id stringlengths 36 36 | document stringlengths 3 3k | metadata stringlengths 23 69 | embeddings listlengths 384 384 |
|---|---|---|---|
19c5c18d-44a0-4954-8649-3b73db501445 | ClickHouse Government on AWS {#clickhouse-government-aws}
Required resources:
-
ECR
to receive the images and Helm charts
- Certificate Authority capable of generating FIPS compliant certificates
-
EKS
cluster with
CNI
,
EBS CSI Driver
,
DNS
,
Cluster Autoscaler
,
IMDS
for authentication and an
OIDC
provider
- Server nodes run Amazon Linux
- Operator requires an x86 node group
- An S3 bucket in the same region as the EKS cluster
- If ingress is required, also configure an NLB
- One AWS role per ClickHouse cluster for clickhouse-server/keeper operations | {"source_file": "03_clickhouse-government.md"} | [
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0.020355183631181717,
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0.03960470110177994,
-0.... |
0021e824-ca6a-4538-83a7-807ef9f21513 | title: 'ClickHouse Private'
slug: /cloud/infrastructure/clickhouse-private
keywords: ['private', 'on-prem']
description: 'Overview of ClickHouse Private offering'
doc_type: 'reference'
import Image from '@theme/IdealImage';
import private_gov_architecture from '@site/static/images/cloud/reference/private-gov-architecture.png';
Overview {#overview}
ClickHouse Private is a self-deployed package consisting of the same proprietary version of ClickHouse that runs on ClickHouse Cloud and our ClickHouse Operator, configured for separation of compute and storage. It is deployed to Kubernetes environments with S3 compatible storage.
This package is currently available for AWS and IBM Cloud, with bare metal deployments coming soon.
:::note Note
ClickHouse Private is designed for large enterprises with the most rigorous compliance requirements, providing full control and management over their dedicated infrastructure. This option is only available by
contacting us
.
:::
Benefits over open-source {#benefits-over-os}
The following features differentiate ClickHouse Private from self-managed open source deployments:
Enhanced performance {#enhanced-performance}
Native separation of compute and storage
Proprietary cloud features such as
shared merge tree
and
warehouse
functionality
Tested and proven through a variety of use cases and conditions {#tested-proven-through-variety-of-use-cases}
Fully tested and validated in ClickHouse Cloud
Full featured roadmap with new features added regularly {#full-featured-roadmap}
Additional features that are coming soon include:
- API to programmatically manage resources
- Automated backups
- Automated vertical scaling operations
- Identity provider integration
Architecture {#architecture}
ClickHouse Private is fully self-contained within your deployment environment and consists of compute managed within Kubernetes and storage within an S3 compatible storage solution.
Onboarding process {#onboarding-process}
Customers can initiate onboarding by reaching out to
us
. For qualified customers, we will provide a detailed environment build guide and access to the images and Helm charts for deployment.
General requirements {#general-requirements}
This section is intended to provide an overview of the resources required to deploy ClickHouse Private. Specific deployment guides are provided as part of onboarding. Instance/ server types and sizes depend on the use case.
ClickHouse Private on AWS {#clickhouse-private-aws}
Required resources:
-
ECR
to receive the images and Helm charts
-
EKS
cluster with
CNI
,
EBS CSI Driver
,
DNS
,
Cluster Autoscaler
,
IMDS
for authentication and an
OIDC
provider
- Server nodes run Amazon Linux
- Operator requires an x86 node group
- An S3 bucket in the same region as the EKS cluster
- If ingress is required, also configure an NLB
- One AWS role per ClickHouse cluster for clickhouse-server/keeper operations | {"source_file": "02_clickhouse-private.md"} | [
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0.023353813216090202,
0.04360238462686539,
-0.... |
d8f0822a-008c-4cbd-a193-00ea97d6a550 | ClickHouse Private on IBM Cloud {#clickhouse-private-ibm-cloud}
Required resources:
-
Container Registry
to receive the images and Helm charts
-
Cloud Kubernetes Service
with
CNI
,
Cloud Block Storage for VPC
,
Cloud DNS
, and
Cluster Autoscaler
- Server nodes run Ubuntu
- Operator requires an x86 node group
-
Cloud Object Storage
in the same region as the Cloud Kubernetes Service cluster
- If ingress is required, also configure an NLB
- One service account per ClickHouse cluster for clickhouse-server/keeper operations | {"source_file": "02_clickhouse-private.md"} | [
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-0.013... |
77099d77-2b6f-4208-9add-df9084efcc07 | title: 'Overview'
slug: /cloud/reference/byoc/overview
sidebar_label: 'Overview'
keywords: ['BYOC', 'cloud', 'bring your own cloud']
description: 'Deploy ClickHouse on your own cloud infrastructure'
doc_type: 'reference'
Overview {#overview}
BYOC (Bring Your Own Cloud) allows you to deploy ClickHouse Cloud on your own cloud infrastructure. This is useful if you have specific requirements or constraints that prevent you from using the ClickHouse Cloud managed service.
If you would like access, please
contact us
.
Refer to our
Terms of Service
for additional information.
BYOC is currently only supported for AWS. You can join the wait list for GCP and Azure
here
.
:::note
BYOC is designed specifically for large-scale deployments, and requires customers to sign a committed contract.
:::
Glossary {#glossary}
ClickHouse VPC:
The VPC owned by ClickHouse Cloud.
Customer BYOC VPC:
The VPC, owned by the customer's cloud account, is provisioned and managed by ClickHouse Cloud and dedicated to a ClickHouse Cloud BYOC deployment.
Customer VPC
Other VPCs owned by the customer cloud account used for applications that need to connect to the Customer BYOC VPC.
Features {#features}
Supported features {#supported-features}
SharedMergeTree
: ClickHouse Cloud and BYOC use the same binary and configuration. Therefore all features from ClickHouse core are supported in BYOC such as SharedMergeTree.
Console access for managing service state
:
Supports operations such as start, stop, and terminate.
View services and status.
Backup and restore.
Manual vertical and horizontal scaling.
Idling.
Warehouses
: Compute-Compute Separation
Zero Trust Network via Tailscale.
Monitoring
:
The Cloud console includes built-in health dashboards for monitoring service health.
Prometheus scraping for centralized monitoring with Prometheus, Grafana, and Datadog. See the
Prometheus documentation
for setup instructions.
VPC Peering.
Integrations
: See the full list on
this page
.
Secure S3.
AWS PrivateLink
.
Planned features (currently unsupported) {#planned-features-currently-unsupported}
AWS KMS
aka CMEK (customer-managed encryption keys)
ClickPipes for ingest
Autoscaling
MySQL interface | {"source_file": "01_overview.md"} | [
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e255aff3-adc0-4273-a604-9c9ea291cc67 | title: 'Architecture'
slug: /cloud/reference/byoc/architecture
sidebar_label: 'Architecture'
keywords: ['BYOC', 'cloud', 'bring your own cloud']
description: 'Deploy ClickHouse on your own cloud infrastructure'
doc_type: 'reference'
import Image from '@theme/IdealImage';
import byoc1 from '@site/static/images/cloud/reference/byoc-1.png';
Architecture {#architecture}
Metrics and logs are stored within the customer's BYOC VPC. Logs are currently stored in locally in EBS. In a future update, logs will be stored in LogHouse, which is a ClickHouse service in the customer's BYOC VPC. Metrics are implemented via a Prometheus and Thanos stack stored locally in the customer's BYOC VPC. | {"source_file": "02_architecture.md"} | [
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0.016103610396385193,
-0... |
32a75cef-944a-451b-9300-3dfdfe6ad603 | title: 'BYOC on AWS Observability'
slug: /cloud/reference/byoc/observability
sidebar_label: 'AWS'
keywords: ['BYOC', 'cloud', 'bring your own cloud', 'AWS']
description: 'Deploy ClickHouse on your own cloud infrastructure'
doc_type: 'reference'
import Image from '@theme/IdealImage';
import byoc4 from '@site/static/images/cloud/reference/byoc-4.png';
import byoc3 from '@site/static/images/cloud/reference/byoc-3.png';
import DeprecatedBadge from '@theme/badges/DeprecatedBadge';
Observability {#observability}
Built-in monitoring tools {#built-in-monitoring-tools}
ClickHouse BYOC provides several approaches for various use cases.
Observability dashboard {#observability-dashboard}
ClickHouse Cloud includes an advanced observability dashboard that displays metrics such as memory usage, query rates, and I/O. This can be accessed in the
Monitoring
section of ClickHouse Cloud web console interface.
Advanced dashboard {#advanced-dashboard}
You can customize a dashboard using metrics from system tables like
system.metrics
,
system.events
, and
system.asynchronous_metrics
and more to monitor server performance and resource utilization in detail.
Access the BYOC Prometheus stack {#prometheus-access}
ClickHouse BYOC deploys a Prometheus stack on your Kubernetes cluster. You may access and scrape the metrics from there and integrate them with your own monitoring stack.
Contact ClickHouse support to enable the Private Load balancer and ask for the URL. Please note that this URL is only accessible via private network and does not support authentication
Sample URL
bash
https://prometheus-internal.<subdomain>.<region>.aws.clickhouse-byoc.com/query
Prometheus Integration {#prometheus-integration}
Please use the Prometheus stack integration in the above section instead. Besides the ClickHouse Server metrics, it provides more metrics including the K8S metrics and metrics from other services.
ClickHouse Cloud provides a Prometheus endpoint that you can use to scrape metrics for monitoring. This allows for integration with tools like Grafana and Datadog for visualization.
Sample request via https endpoint /metrics_all
bash
curl --user <username>:<password> https://i6ro4qarho.mhp0y4dmph.us-west-2.aws.byoc.clickhouse.cloud:8443/metrics_all
Sample Response
```bash
HELP ClickHouse_CustomMetric_StorageSystemTablesS3DiskBytes The amount of bytes stored on disk
s3disk
in system database
TYPE ClickHouse_CustomMetric_StorageSystemTablesS3DiskBytes gauge
ClickHouse_CustomMetric_StorageSystemTablesS3DiskBytes{hostname="c-jet-ax-16-server-43d5baj-0"} 62660929
HELP ClickHouse_CustomMetric_NumberOfBrokenDetachedParts The number of broken detached parts
TYPE ClickHouse_CustomMetric_NumberOfBrokenDetachedParts gauge
ClickHouse_CustomMetric_NumberOfBrokenDetachedParts{hostname="c-jet-ax-16-server-43d5baj-0"} 0
HELP ClickHouse_CustomMetric_LostPartCount The age of the oldest mutation (in seconds) | {"source_file": "01_aws.md"} | [
-0.01881493628025055,
0.005326196551322937,
-0.10055641829967499,
0.016599133610725403,
0.09080340713262558,
-0.05678335949778557,
0.053430065512657166,
-0.014664595015347004,
-0.008072535507380962,
0.08945784717798233,
0.057881079614162445,
-0.03213915228843689,
0.07643505930900574,
0.003... |
801e1288-19a8-4041-b89c-c4a40a453626 | ClickHouse_CustomMetric_NumberOfBrokenDetachedParts{hostname="c-jet-ax-16-server-43d5baj-0"} 0
HELP ClickHouse_CustomMetric_LostPartCount The age of the oldest mutation (in seconds)
TYPE ClickHouse_CustomMetric_LostPartCount gauge
ClickHouse_CustomMetric_LostPartCount{hostname="c-jet-ax-16-server-43d5baj-0"} 0
HELP ClickHouse_CustomMetric_NumberOfWarnings The number of warnings issued by the server. It usually indicates about possible misconfiguration
TYPE ClickHouse_CustomMetric_NumberOfWarnings gauge
ClickHouse_CustomMetric_NumberOfWarnings{hostname="c-jet-ax-16-server-43d5baj-0"} 2
HELP ClickHouseErrorMetric_FILE_DOESNT_EXIST FILE_DOESNT_EXIST
TYPE ClickHouseErrorMetric_FILE_DOESNT_EXIST counter
ClickHouseErrorMetric_FILE_DOESNT_EXIST{hostname="c-jet-ax-16-server-43d5baj-0",table="system.errors"} 1
HELP ClickHouseErrorMetric_UNKNOWN_ACCESS_TYPE UNKNOWN_ACCESS_TYPE
TYPE ClickHouseErrorMetric_UNKNOWN_ACCESS_TYPE counter
ClickHouseErrorMetric_UNKNOWN_ACCESS_TYPE{hostname="c-jet-ax-16-server-43d5baj-0",table="system.errors"} 8
HELP ClickHouse_CustomMetric_TotalNumberOfErrors The total number of errors on server since the last restart
TYPE ClickHouse_CustomMetric_TotalNumberOfErrors gauge
ClickHouse_CustomMetric_TotalNumberOfErrors{hostname="c-jet-ax-16-server-43d5baj-0"} 9
```
Authentication
A ClickHouse username and password pair can be used for authentication. We recommend creating a dedicated user with minimal permissions for scraping metrics. At minimum, a
READ
permission is required on the
system.custom_metrics
table across replicas. For example:
sql
GRANT REMOTE ON *.* TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_custom_metrics_tables TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_database_replicated_recovery_time TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_failed_mutations TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_group TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_shared_catalog_recovery_time TO scrapping_user;
GRANT SELECT ON system._custom_metrics_dictionary_table_read_only_duration_seconds TO scrapping_user;
GRANT SELECT ON system._custom_metrics_view_error_metrics TO scrapping_user;
GRANT SELECT ON system._custom_metrics_view_histograms TO scrapping_user;
GRANT SELECT ON system._custom_metrics_view_metrics_and_events TO scrapping_user;
GRANT SELECT(description, metric, value) ON system.asynchronous_metrics TO scrapping_user;
GRANT SELECT ON system.custom_metrics TO scrapping_user;
GRANT SELECT(name, value) ON system.errors TO scrapping_user;
GRANT SELECT(description, event, value) ON system.events TO scrapping_user;
GRANT SELECT(description, labels, metric, value) ON system.histogram_metrics TO scrapping_user;
GRANT SELECT(description, metric, value) ON system.metrics TO scrapping_user;
Configuring Prometheus | {"source_file": "01_aws.md"} | [
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0.028713423758745193,
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0.06566671282052994,
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0.041135624051094055,
0.0... |
4570e3cb-8a7e-45c4-9325-6c891ecade59 | Configuring Prometheus
An example configuration is shown below. The
targets
endpoint is the same one used for accessing the ClickHouse service.
```bash
global:
scrape_interval: 15s
scrape_configs:
- job_name: "prometheus"
static_configs:
- targets: ["localhost:9090"]
- job_name: "clickhouse"
static_configs:
- targets: ["
.
.aws.byoc.clickhouse.cloud:8443"]
scheme: https
metrics_path: "/metrics_all"
basic_auth:
username:
password:
honor_labels: true
```
Please also see
this blog post
and the
Prometheus setup docs for ClickHouse
. | {"source_file": "01_aws.md"} | [
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2969d0f8-5000-428c-93c7-7a62609ff2d4 | title: 'BYOC Onboarding for AWS'
slug: /cloud/reference/byoc/onboarding/aws
sidebar_label: 'AWS'
keywords: ['BYOC', 'cloud', 'bring your own cloud', 'AWS']
description: 'Deploy ClickHouse on your own cloud infrastructure'
doc_type: 'reference'
import Image from '@theme/IdealImage';
import byoc_vpcpeering from '@site/static/images/cloud/reference/byoc-vpcpeering-1.png';
import byoc_vpcpeering2 from '@site/static/images/cloud/reference/byoc-vpcpeering-2.png';
import byoc_vpcpeering3 from '@site/static/images/cloud/reference/byoc-vpcpeering-3.png';
import byoc_vpcpeering4 from '@site/static/images/cloud/reference/byoc-vpcpeering-4.png';
import byoc_subnet_1 from '@site/static/images/cloud/reference/byoc-subnet-1.png';
import byoc_subnet_2 from '@site/static/images/cloud/reference/byoc-subnet-2.png';
import byoc_s3_endpoint from '@site/static/images/cloud/reference/byoc-s3-endpoint.png'
Onboarding process {#onboarding-process}
Customers can initiate the onboarding process by reaching out to
us
. Customers need to have a dedicated AWS account and know the region they will use. At this time, we are allowing users to launch BYOC services only in the regions that we support for ClickHouse Cloud.
Prepare an AWS account {#prepare-an-aws-account}
Customers are recommended to prepare a dedicated AWS account for hosting the ClickHouse BYOC deployment to ensure better isolation. However, using a shared account and an existing VPC is also possible. See the details in
Setup BYOC Infrastructure
below.
With this account and the initial organization admin email, you can contact ClickHouse support.
Initialize BYOC setup {#initialize-byoc-setup}
The initial BYOC setup can be performed using either a CloudFormation template or a Terraform module. Both approaches create the same IAM role, enabling BYOC controllers from ClickHouse Cloud to manage your infrastructure. Note that S3, VPC, and compute resources required for running ClickHouse are not included in this initial setup.
CloudFormation Template {#cloudformation-template}
BYOC CloudFormation template
Terraform Module {#terraform-module}
BYOC Terraform module
hcl
module "clickhouse_onboarding" {
source = "https://s3.us-east-2.amazonaws.com/clickhouse-public-resources.clickhouse.cloud/tf/byoc.tar.gz"
byoc_env = "production"
}
Set up BYOC infrastructure {#setup-byoc-infrastructure}
After creating the CloudFormation stack, you will be prompted to set up the infrastructure, including S3, VPC, and the EKS cluster, from the cloud console. Certain configurations must be determined at this stage, as they cannot be changed later. Specifically:
The region you want to use
, you can choose one of any
public regions
we have for ClickHouse Cloud. | {"source_file": "01_aws.md"} | [
-0.038925718516111374,
-0.03761010989546776,
-0.053062696009874344,
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0.10804283618927002,
0.00313... |
6a3b66dc-ffb7-4c56-a2b5-3910488eea31 | The region you want to use
, you can choose one of any
public regions
we have for ClickHouse Cloud.
The VPC CIDR range for BYOC
: By default, we use
10.0.0.0/16
for the BYOC VPC CIDR range. If you plan to use VPC peering with another account, ensure the CIDR ranges do not overlap. Allocate a proper CIDR range for BYOC, with a minimum size of
/22
to accommodate necessary workloads.
Availability Zones for BYOC VPC
: If you plan to use VPC peering, aligning availability zones between the source and BYOC accounts can help reduce cross-AZ traffic costs. In AWS, availability zone suffixes (
a, b, c
) may represent different physical zone IDs across accounts. See the
AWS guide
for details.
Customer-managed VPC {#customer-managed-vpc}
By default, ClickHouse Cloud will provision a dedicated VPC for better isolation in your BYOC deployment. However, you can also use an existing VPC in your account. This requires specific configuration and must be coordinated through ClickHouse Support.
Configure Your Existing VPC
1. Allocate at least 3 private subnets across 3 different availability zones for ClickHouse Cloud to use.
2. Ensure each subnet has a minimum CIDR range of
/23
(e.g., 10.0.0.0/23) to provide sufficient IP addresses for the ClickHouse deployment.
3. Add the tag
kubernetes.io/role/internal-elb=1
to each subnet to enable proper load balancer configuration.
Configure S3 Gateway Endpoint
If your VPC doesn't already have an S3 Gateway Endpoint configured, you'll need to create one to enable secure, private communication between your VPC and Amazon S3. This endpoint allows your ClickHouse services to access S3 without going through the public internet. Please refer to the screenshot below for an example configuration.
Contact ClickHouse Support
Create a support ticket with the following information:
Your AWS account ID
The AWS region where you want to deploy the service
Your VPC ID
The Private Subnet IDs you've allocated for ClickHouse
The availability zones these subnets are in
Optional: Setup VPC Peering {#optional-setup-vpc-peering}
To create or delete VPC peering for ClickHouse BYOC, follow the steps:
Step 1: Enable private load balancer for ClickHouse BYOC {#step-1-enable-private-load-balancer-for-clickhouse-byoc}
Contact ClickHouse Support to enable Private Load Balancer.
Step 2 Create a peering connection {#step-2-create-a-peering-connection}
Navigate to the VPC Dashboard in ClickHouse BYOC account.
Select Peering Connections.
Click Create Peering Connection
Set the VPC Requester to the ClickHouse VPC ID.
Set the VPC Accepter to the target VPC ID. (Select another account if applicable)
Click Create Peering Connection.
Step 3 Accept the peering connection request {#step-3-accept-the-peering-connection-request} | {"source_file": "01_aws.md"} | [
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0.000... |
406814f5-8b16-46f8-8858-02fc83981d30 | Click Create Peering Connection.
Step 3 Accept the peering connection request {#step-3-accept-the-peering-connection-request}
Go to the peering account, in the (VPC -> Peering connections -> Actions -> Accept request) page customer can approve this VPC peering request.
Step 4 Add destination to ClickHouse VPC route tables {#step-4-add-destination-to-clickhouse-vpc-route-tables}
In ClickHouse BYOC account,
1. Select Route Tables in the VPC Dashboard.
2. Search for the ClickHouse VPC ID. Edit each route table attached to the private subnets.
3. Click the Edit button under the Routes tab.
4. Click Add another route.
5. Enter the CIDR range of the target VPC for the Destination.
6. Select “Peering Connection” and the ID of the peering connection for the Target.
Step 5 Add destination to the target VPC route tables {#step-5-add-destination-to-the-target-vpc-route-tables}
In the peering AWS account,
1. Select Route Tables in the VPC Dashboard.
2. Search for the target VPC ID.
3. Click the Edit button under the Routes tab.
4. Click Add another route.
5. Enter the CIDR range of the ClickHouse VPC for the Destination.
6. Select “Peering Connection” and the ID of the peering connection for the Target.
Step 6: Edit security group to allow peered VPC access {#step-6-edit-security-group-to-allow-peered-vpc-access}
In the ClickHouse BYOC account, you need to update the Security Group settings to allow traffic from your peered VPC. Please contact ClickHouse Support to request the addition of inbound rules that include the CIDR ranges of your peered VPC.
The ClickHouse service should now be accessible from the peered VPC.
To access ClickHouse privately, a private load balancer and endpoint are provisioned for secure connectivity from the user's peered VPC. The private endpoint follows the public endpoint format with a
-private
suffix. For example:
-
Public endpoint
:
h5ju65kv87.mhp0y4dmph.us-west-2.aws.byoc.clickhouse.cloud
-
Private endpoint
:
h5ju65kv87-private.mhp0y4dmph.us-west-2.aws.byoc.clickhouse.cloud
Optional, after verifying that peering is working, you can request the removal of the public load balancer for ClickHouse BYOC.
Upgrade process {#upgrade-process}
We regularly upgrade the software, including ClickHouse database version upgrades, ClickHouse Operator, EKS, and other components.
While we aim for seamless upgrades (e.g., rolling upgrades and restarts), some, such as ClickHouse version changes and EKS node upgrades, may impact service. Customers can specify a maintenance window (e.g., every Tuesday at 1:00 a.m. PDT), ensuring such upgrades occur only during the scheduled time.
:::note
Maintenance windows do not apply to security and vulnerability fixes. These are handled as off-cycle upgrades, with timely communication to coordinate a suitable time and minimize operational impact.
:::
CloudFormation IAM roles {#cloudformation-iam-roles} | {"source_file": "01_aws.md"} | [
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aaec5048-983a-451c-b3c3-27b90d0dcd95 | CloudFormation IAM roles {#cloudformation-iam-roles}
Bootstrap IAM role {#bootstrap-iam-role}
The bootstrap IAM role has the following permissions:
EC2 and VPC operations
: Required for setting up VPC and EKS clusters.
S3 operations (e.g.,
s3:CreateBucket
)
: Needed to create buckets for ClickHouse BYOC storage.
route53:*
permissions
: Required for external DNS to configure records in Route 53.
IAM operations (e.g.,
iam:CreatePolicy
)
: Needed for controllers to create additional roles (see the next section for details).
EKS operations
: Limited to resources with names starting with the
clickhouse-cloud
prefix.
Additional IAM roles created by the controller {#additional-iam-roles-created-by-the-controller}
In addition to the
ClickHouseManagementRole
created via CloudFormation, the controller will create several additional roles.
These roles are assumed by applications running within the customer's EKS cluster:
-
State Exporter Role
- ClickHouse component that reports service health information to ClickHouse Cloud.
- Requires permission to write to an SQS queue owned by ClickHouse Cloud.
-
Load-Balancer Controller
- Standard AWS load balancer controller.
- EBS CSI Controller to manage volumes for ClickHouse services.
-
External-DNS
- Propagates DNS configurations to Route 53.
-
Cert-Manager
- Provisions TLS certificates for BYOC service domains.
-
Cluster Autoscaler
- Adjusts the node group size as needed.
K8s-control-plane
and
k8s-worker
roles are meant to be assumed by AWS EKS services.
Lastly,
data-plane-mgmt
allows a ClickHouse Cloud Control Plane component to reconcile necessary custom resources, such as
ClickHouseCluster
and the Istio Virtual Service/Gateway.
Network boundaries {#network-boundaries}
This section covers different network traffic to and from the customer BYOC VPC:
Inbound
: Traffic entering the customer BYOC VPC.
Outbound
: Traffic originating from the customer BYOC VPC and sent to an external destination.
Public
: A network endpoint accessible from the public internet.
Private
: A network endpoint accessible only through private connections, such as VPC peering, VPC Private Link, or Tailscale.
Istio ingress is deployed behind an AWS NLB to accept ClickHouse client traffic.
Inbound, Public (can be Private)
The Istio ingress gateway terminates TLS. The certificate, provisioned by CertManager with Let's Encrypt, is stored as a secret within the EKS cluster. Traffic between Istio and ClickHouse is
encrypted by AWS
since they reside in the same VPC.
By default, ingress is publicly accessible with IP allow list filtering. Customers can configure VPC peering to make it private and disable public connections. We highly recommend setting up an
IP filter
to restrict access.
Troubleshooting access {#troubleshooting-access}
Inbound, Public (can be Private) | {"source_file": "01_aws.md"} | [
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0fc3b226-250c-4e05-b2b5-01d286bb73bc | Troubleshooting access {#troubleshooting-access}
Inbound, Public (can be Private)
ClickHouse Cloud engineers require troubleshooting access via Tailscale. They are provisioned with just-in-time certificate-based authentication for BYOC deployments.
Billing scraper {#billing-scraper}
Outbound, Private
The Billing scraper collects billing data from ClickHouse and sends it to an S3 bucket owned by ClickHouse Cloud.
It runs as a sidecar alongside the ClickHouse server container, periodically scraping CPU and memory metrics. Requests within the same region are routed through VPC gateway service endpoints.
Alerts {#alerts}
Outbound, Public
AlertManager is configured to send alerts to ClickHouse Cloud when the customer's ClickHouse cluster is unhealthy.
Metrics and logs are stored within the customer's BYOC VPC. Logs are currently stored locally in EBS. In a future update, they will be stored in LogHouse, a ClickHouse service within the BYOC VPC. Metrics use a Prometheus and Thanos stack, stored locally in the BYOC VPC.
Service state {#service-state}
Outbound
State Exporter sends ClickHouse service state information to an SQS owned by ClickHouse Cloud. | {"source_file": "01_aws.md"} | [
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a0d11f0f-89b3-4626-9ed1-8d779d3413a1 | title: 'BYOC on AWS FAQ'
slug: /cloud/reference/byoc/faq/aws
sidebar_label: 'AWS'
keywords: ['BYOC', 'cloud', 'bring your own cloud', 'AWS']
description: 'Deploy ClickHouse on your own cloud infrastructure'
doc_type: 'reference'
FAQ {#faq}
Compute {#compute}
Can I create multiple services in this single EKS cluster?
Yes. The infrastructure only needs to be provisioned once for every AWS account and region combination.
Which regions do you support for BYOC?
BYOC supports the same set of [regions](/cloud/reference/supported-regions#aws-regions ) as ClickHouse Cloud.
Will there be some resource overhead? What are the resources needed to run services other than ClickHouse instances?
Besides Clickhouse instances (ClickHouse servers and ClickHouse Keeper), we run services such as `clickhouse-operator`, `aws-cluster-autoscaler`, Istio etc. and our monitoring stack.
Currently, we have three m5.xlarge nodes (one for each AZ) in a dedicated node group to run those workloads.
Network and security {#network-and-security}
Can we revoke permissions set up during installation after setup is complete?
This is currently not possible.
Have you considered some future security controls for ClickHouse engineers to access customer infra for troubleshooting?
Yes. Implementing a customer controlled mechanism where customers can approve engineers' access to the cluster is on our roadmap. At the moment, engineers must go through our internal escalation process to gain just-in-time access to the cluster. This is logged and audited by our security team.
What is the size of the VPC IP range created?
By default, we use `10.0.0.0/16` for BYOC VPC. We recommend reserving at least /22 for potential future scaling,
but if you prefer to limit the size, it is possible to use /23 if it is likely that you will be limited
to 30 server pods.
Can I decide maintenance frequency?
Contact support to schedule maintenance windows. Please expect a minimum of a weekly update schedule.
Uptime SLAs {#uptime-sla}
Does ClickHouse offer an uptime SLA for BYOC?
No, since the data plane is hosted in the customer's cloud environment, service availability depends on resources not in ClickHouse's control. Therefore, ClickHouse does not offer a formal uptime SLA for BYOC deployments. If you have additional questions, please contact support@clickhouse.com. | {"source_file": "01_aws.md"} | [
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40617e60-06de-44d3-a54e-745c9f04881c | sidebar_label: 'Backup or restore using commands'
slug: /cloud/manage/backups/backup-restore-via-commands
title: 'Take a backup or restore a backup using commands'
description: 'Page describing how to take a backup or restore a backup with your own bucket using commands'
sidebar_position: 3
doc_type: 'guide'
keywords: ['backups', 'disaster recovery', 'data protection', 'restore', 'cloud features']
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
Take a backup or restore a backup using commands {#commands-experience}
Users can utilize
BACKUP
and
RESTORE
commands to export backups to their storage buckets,
in addition to backing up or restoring
via user interface
.
Commands for all three CSPs are given in this guide.
Requirements {#requirements}
You will need the following details to export/restore backups to your own CSP storage bucket:
1. AWS S3 endpoint, in the format:
s3://<bucket_name>.s3.amazonaws.com/<optional_directory>
For example:
s3://testchbackups.s3.amazonaws.com/
Where:
*
testchbackups
is the name of the S3 bucket to export backups to.
*
backups
is an optional subdirectory.
2. AWS access key and secret. AWS role based authentication is also supported and can be used in place of AWS access key and secret as described in the section above.
1. GCS endpoint, in the format:
https://storage.googleapis.com/<bucket_name>/
2. Access HMAC key and HMAC secret.
1. Azure storage connection string.
2. Azure container name in the storage account.
3. Azure Blob within the container.
Backup / Restore specific DB {#backup_restore_db}
Here we show the backup and restore of a
single
database.
See the
backup command summary
for full backup and restore commands.
AWS S3 {#aws-s3-bucket}
sql
BACKUP DATABASE test_backups
TO S3(
'https://testchbackups.s3.amazonaws.com/<uuid>',
'<key id>',
'<key secret>'
)
Where
uuid
is a unique identifier, used to differentiate a set of backups.
:::note
You will need to use a different uuid for each new backup in this subdirectory, otherwise you will get a
BACKUP_ALREADY_EXISTS
error.
For example, if you are taking daily backups, you will need to use a new uuid each day.
:::
sql
RESTORE DATABASE test_backups
FROM S3(
'https://testchbackups.s3.amazonaws.com/<uuid>',
'<key id>',
'<key secret>'
)
Google Cloud Storage (GCS) {#google-cloud-storage}
sql
BACKUP DATABASE test_backups
TO S3(
'https://storage.googleapis.com/<bucket>/<uuid>',
'<hmac-key>',
'<hmac-secret>'
)
Where
uuid
is a unique identifier, used to identify the backup.
:::note
You will need to use a different uuid for each new backup in this subdirectory, otherwise you will get a
BACKUP_ALREADY_EXISTS
error.
For example, if you are taking daily backups, you will need to use a new uuid each day.
::: | {"source_file": "03_backup_restore_using_commands.md"} | [
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7bf8c50b-fd47-4f7d-b96f-22e3773cb27f | sql
RESTORE DATABASE test_backups
FROM S3(
'https://storage.googleapis.com/<bucket>/<uuid>',
'<hmac-key>',
'<hmac-secret>'
)
Azure Blob Storage {#azure-blob-storage}
sql
BACKUP DATABASE test_backups
TO AzureBlobStorage(
'<AzureBlobStorage endpoint connection string>',
'<container>',
'<blob>/<>'
)
Where
uuid
is a unique identifier, used to identify the backup.
:::note
You will need to use a different uuid for each new backup in this subdirectory, otherwise you will get a
BACKUP_ALREADY_EXISTS
error.
For example, if you are taking daily backups, you will need to use a new uuid each day.
:::
sql
RESTORE DATABASE test_backups
FROM AzureBlobStorage(
'<AzureBlobStorage endpoint connection string>',
'<container>',
'<blob>/<uuid>'
)
Backup / Restore entire service {#backup_restore_entire_service}
For backing up the entire service, use the commands below.
This backup will contain all user data and system data for created entities, settings profiles, role policies, quotas, and functions.
We list these here for AWS S3.
You can utilize these commands with the syntax described above to take backups for GCS and Azure Blob storage.
sql
BACKUP
TABLE system.users,
TABLE system.roles,
TABLE system.settings_profiles,
TABLE system.row_policies,
TABLE system.quotas,
TABLE system.functions,
ALL EXCEPT DATABASES INFORMATION_SCHEMA, information_schema, system
TO S3(
'https://testchbackups.s3.amazonaws.com/<uuid>',
'<key id>',
'<key secret>'
)
where
uuid
is a unique identifier, used to identify the backup.
sql
RESTORE ALL
FROM S3(
'https://testchbackups.s3.amazonaws.com/<uuid>',
'<key id>',
'<key secret>'
)
FAQ {#backups-faq}
What happens to the backups in my cloud object storage? Are they cleaned up by ClickHouse at some point?
We provide you the ability to export backups to your bucket, however, we do not clean up or delete any of the backups once written. You are responsible for managing the lifecycle of the backups in your bucket, including deleting, or archiving as needed, or moving to cheaper storage to optimize overall cost.
What happens to the restore process if I move some of the existing backups to another location?
If any backups are moved to another location, the restore command will need to be updated to reference the new location where the backups are stored.
What if I change my credentials required to access the object storage?
You will need to update the changed credentials in the UI, for backups to start happening successfully again.
What if I change the location to export my external backups to?
You will need to update the new location in the UI, and backups will start happening to the new location. The old backups will stay in the original location.
How can I disable external backups on a service that I enabled them for? | {"source_file": "03_backup_restore_using_commands.md"} | [
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af6a6bba-b933-4cd3-a881-266536d8582f | How can I disable external backups on a service that I enabled them for?
To disable external backups for a service, go to the service setting screen, and click on Change external backup. In the subsequent screen, click on Remove setup to disable external backups for the service. | {"source_file": "03_backup_restore_using_commands.md"} | [
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3995a837-aa1d-4abf-b6ed-fbe2e5592bd4 | sidebar_label: 'Export backups'
slug: /cloud/manage/backups/export-backups-to-own-cloud-account
title: 'Export Backups to your Own Cloud Account'
description: 'Describes how to export backups to your own Cloud account'
doc_type: 'guide'
import EnterprisePlanFeatureBadge from '@theme/badges/EnterprisePlanFeatureBadge'
ClickHouse Cloud supports taking backups to your own cloud service provider (CSP) account (AWS S3, Google Cloud Storage, or Azure Blob Storage).
For details of how ClickHouse Cloud backups work, including "full" vs. "incremental" backups, see the
backups
docs.
In this guide, we show examples of how to take full and incremental backups to AWS, GCP, Azure object storage as well as how to restore from the backups.
:::note
Users should be aware that any usage where backups are being exported to a different region in the same cloud provider, will incur
data transfer
charges. Currently we do not support cross cloud backups.
:::
Requirements {#requirements}
You will need the following details to export/restore backups to your own CSP storage bucket.
AWS {#aws}
AWS S3 endpoint, in the format:
text
s3://<bucket_name>.s3.amazonaws.com/<directory>
For example:
text
s3://testchbackups.s3.amazonaws.com/backups/
Where:
-
testchbackups
is the name of the S3 bucket to export backups to.
-
backups
is an optional subdirectory.
AWS access key and secret. AWS role based authentication is also supported and can be used in place of AWS access key and secret.
:::note
In order to use role based authentication, please follow the Secure s3
setup
. In addition, you will need to add
s3:PutObject
, and
s3:DeleteObject
permissions to the IAM policy described
here.
:::
Azure {#azure}
Azure storage connection string.
Azure container name in the storage account.
Azure Blob within the container.
Google Cloud Storage (GCS) {#google-cloud-storage-gcs}
GCS endpoint, in the format:
text
https://storage.googleapis.com/<bucket_name>/
2. Access HMAC key and HMAC secret.
Backup / Restore
Backup / Restore to AWS S3 Bucket {#backup--restore-to-aws-s3-bucket}
Take a DB backup {#take-a-db-backup}
Full Backup
sql
BACKUP DATABASE test_backups
TO S3('https://testchbackups.s3.amazonaws.com/backups/<uuid>', '<key id>', '<key secret>')
Where
uuid
is a unique identifier, used to differentiate a set of backups.
:::note
You will need to use a different UUID for each new backup in this subdirectory, otherwise you will get a
BACKUP_ALREADY_EXISTS
error.
For example, if you are taking daily backups, you will need to use a new UUID each day.
:::
Incremental Backup
sql
BACKUP DATABASE test_backups
TO S3('https://testchbackups.s3.amazonaws.com/backups/<uuid>', '<key id>', '<key secret>')
SETTINGS base_backup = S3('https://testchbackups.s3.amazonaws.com/backups/<base-backup-uuid>', '<key id>', '<key secret>')
Restore from a backup {#restore-from-a-backup} | {"source_file": "01_export-backups-to-own-cloud-account.md"} | [
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51c350c4-f941-4a5a-abb3-98c59e6da213 | Restore from a backup {#restore-from-a-backup}
sql
RESTORE DATABASE test_backups
AS test_backups_restored
FROM S3('https://testchbackups.s3.amazonaws.com/backups/<uuid>', '<key id>', '<key secret>')
See:
Configuring BACKUP/RESTORE to use an S3 Endpoint
for more details.
Backup / Restore to Azure Blob Storage {#backup--restore-to-azure-blob-storage}
Take a DB backup {#take-a-db-backup-1}
Full Backup
sql
BACKUP DATABASE test_backups
TO AzureBlobStorage('<AzureBlobStorage endpoint connection string>', '<container>', '<blob>/<uuid>');
Where
uuid
is a unique identifier, used to differentiate a set of backups.
Incremental Backup
sql
BACKUP DATABASE test_backups
TO AzureBlobStorage('<AzureBlobStorage endpoint connection string>', '<container>', '<blob>/<uuid>/my_incremental')
SETTINGS base_backup = AzureBlobStorage('<AzureBlobStorage endpoint connection string>', '<container>', '<blob>/<uuid>')
Restore from a backup {#restore-from-a-backup-1}
sql
RESTORE DATABASE test_backups
AS test_backups_restored_azure
FROM AzureBlobStorage('<AzureBlobStorage endpoint connection string>', '<container>', '<blob>/<uuid>')
See:
Configuring BACKUP/RESTORE to use an S3 Endpoint
for more details.
Backup / Restore to Google Cloud Storage (GCS) {#backup--restore-to-google-cloud-storage-gcs}
Take a DB backup {#take-a-db-backup-2}
Full Backup
sql
BACKUP DATABASE test_backups
TO S3('https://storage.googleapis.com/<bucket>/<uuid>', <hmac-key>', <hmac-secret>)
Where
uuid
is a unique identifier, used to differentiate a set of backups.
Incremental Backup
sql
BACKUP DATABASE test_backups
TO S3('https://storage.googleapis.com/test_gcs_backups/<uuid>/my_incremental', 'key', 'secret')
SETTINGS base_backup = S3('https://storage.googleapis.com/test_gcs_backups/<uuid>', 'key', 'secret')
Restore from a backup {#restore-from-a-backup-2}
sql
RESTORE DATABASE test_backups
AS test_backups_restored_gcs
FROM S3('https://storage.googleapis.com/test_gcs_backups/<uuid>', 'key', 'secret') | {"source_file": "01_export-backups-to-own-cloud-account.md"} | [
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50d086e3-0b8e-4395-b4f9-ee82a118bf75 | sidebar_label: 'Backup or restore using UI'
slug: /cloud/manage/backups/backup-restore-via-ui
title: 'Take a backup or restore a backup from the UI'
description: 'Page describing how to take a backup or restore a backup from the UI with your own bucket'
sidebar_position: 2
doc_type: 'guide'
keywords: ['backups', 'disaster recovery', 'data protection', 'restore', 'cloud features']
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Backup / restore via user-interface {#ui-experience}
AWS {#AWS}
Taking backups to AWS {#taking-backups-to-aws}
1. Steps to follow in AWS {#aws-steps}
:::note
These steps are similar to the secure s3 setup as described in
"Accessing S3 data securely"
, however, there are additional actions required in the role permissions
:::
Follow the steps below on your AWS account:
Create an AWS S3 bucket {#create-s3-bucket}
Create an AWS S3 bucket in your account where you want to export backups.
Create an IAM role {#create-iam-role}
AWS uses role based authentication, so create an IAM role that the ClickHouse Cloud service will be able to assume into, to write to this bucket.
a. Obtain the ARN from the ClickHouse Cloud service settings page, under Network security information, which looks similar to this:
b. For this role create the trust policy as follows:
json
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "backup service",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam::463754717262:role/CH-S3-bordeaux-ar-90-ue2-29-Role"
},
"Action": "sts:AssumeRole"
}
]
}
Update permissions for role {#update-permissions-for-role}
You will also need to set the permissions for this role so this ClickHouse Cloud service can write to the S3 bucket.
This is done by creating a permissions policy for the role with a JSON similar to this one, where you substitute in your bucket ARN for the resource in both places. | {"source_file": "02_backup_restore_from_ui.md"} | [
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0.05686300992965698,
0.0951547771692276,
0.01646304875612259,
0.03460113704204559,
0.03215394169092178,
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0.02452264539897442,
0.010271218605339527,
0.025615308433771133,
0.08433499187231064,
-0.0727614... |
3fd29360-2563-466c-bd68-bc799a73ec04 | json
{
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"s3:GetBucketLocation",
"s3:ListBucket"
],
"Resource": [
"arn:aws:s3:::byob-ui"
],
"Effect": "Allow"
},
{
"Action": [
"s3:Get*",
"s3:List*",
"s3:PutObject"
],
"Resource": [
"arn:aws:s3:::byob-ui/*"
],
"Effect": "Allow"
},
{
"Action": [
"s3:DeleteObject"
],
"Resource": [
"arn:aws:s3:::byob-ui/*/.lock"
],
"Effect": "Allow"
}
]
}
2. Steps to follow in ClickHouse Cloud {#cloud-steps}
Follow the steps below in the ClickHouse Cloud console to configure the external bucket:
Change external backup {#configure-external-bucket}
On the Settings page, click on Set up external backup:
Configure AWS IAM Role ARN and S3 bucket details {#configure-aws-iam-role-arn-and-s3-bucket-details}
On the next screen provide the AWS IAM Role ARN you just created and the S3 bucket URL in the following format:
Save changes {#save-changes}
Click on “Save External Bucket” to save the settings
Changing the backup schedule from the default schedule {#changing-the-backup-schedule}
External Backups will now happen in your bucket on the default schedule.
Alternatively, you can configure the backup schedule from the “Settings” page.
If configured differently, the custom schedule is used to write backups to your
bucket and the default schedule (backups every 24 hours) is used for backups in
the ClickHouse cloud owned bucket.
View backups stored in your bucket {#view-backups-stored-in-your-bucket}
The Backups page will display these backups in your bucket in a separate table
as shown below:
Restoring backups from AWS {#restoring-backups-from-aws}
Follow the steps below to restore backups from AWS:
Create a new service to restore to {#create-new-service-to-restore-to}
Create a new service to restore the backup to.
Add service ARN {#add-service-arn}
Add the newly created service’s ARN (from the service settings page in Clickhouse
Cloud console) to the trust policy for the IAM role. This is the same as the
second step
in the AWS Steps section above. This is required
so the new service can access the S3 bucket.
Get SQL command used to restore backup {#obtain-sql-command-to-restore-backup}
Click on the “access or restore a backup” link above the list of backups in the
UI to get the SQL command to restore the backup. The command will look like this:
:::warning Moving backups to another location
If you move the backups to another location, you will need to customize the restore command to reference the new location.
::: | {"source_file": "02_backup_restore_from_ui.md"} | [
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8a16f007-eafd-40f7-99bd-fb0ded336ca6 | :::warning Moving backups to another location
If you move the backups to another location, you will need to customize the restore command to reference the new location.
:::
:::tip ASYNC command
For the Restore command you can also optionally add an
ASYNC
command at the end for large restores.
This allows the restores to happen asynchronously, so that if connection is lost, the restore keeps running.
It is important to note that the ASYNC command immediately returns a status of success.
This does not mean the restore was successful.
You will need to monitor the
system.backups
table to see if the restore has finished and if it succeeded or failed.
:::
Run the restore command {#run-the-restore-command}
Run the restore command from the SQL console in the newly created service to
restore the backup.
GCP {#gcp}
Taking backups to GCP {#taking-backups-to-gcp}
Follow the steps below to take backups to GCP:
Steps to follow in GCP {#gcp-steps-to-follow}
Create a GCP storage bucket {#create-a-gcp-storage-bucket}
Create a storage bucket in your GCP account to export backups to.
Generate an HMAC Key and Secret {#generate-an-hmac-key-and-secret}
Generate an HMAC Key and Secret, which is required for password-based authentication. Follow the steps below to generate the keys:
a. Create a service account
I. Navigate to the IAM & Admin section in the Google Cloud Console and select
Service Accounts
.
II. Click
Create Service Account
and provide a name and ID. Click
Create and Continue
.
III. Grant the Storage Object User role to this service account.
IV. Click
Done
to finalize the service account creation.
b. Generate the HMAC key
I. Go to Cloud Storage in the Google Cloud Console, and select
Settings
II Go to the Interoperability tab.
III. In the
Service account HMAC
section, click
Create a key for a service account
.
IV. Choose the service account you created in the previous step from the dropdown menu.
V. Click
Create key
.
c. Securely store the credentials:
I. The system will display the Access ID (your HMAC key) and the Secret (your HMAC secret). Save these values, as
the secret will not be displayed again after you close this window.
Steps to follow in ClickHouse Cloud {#gcp-cloud-steps}
Follow the steps below in the ClickHouse Cloud console to configure the external bucket:
Change external backup {#gcp-configure-external-bucket}
On the
Settings
page, click on
Change external backup
Configure GCP HMAC Key and Secret {#gcp-configure-gcp-hmac-key-and-secret}
In the popup dialogue, provide the GCP bucket path, HMAC key and Secret created in the previous section.
Save external bucket {#gcp-save-external-bucket}
Click on
Save External Bucket
to save the settings.
Changing the backup schedule from the default schedule {#gcp-changing-the-backup-schedule} | {"source_file": "02_backup_restore_from_ui.md"} | [
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f41db6a3-8aa2-4bb0-8b75-532aae54a374 | Save external bucket {#gcp-save-external-bucket}
Click on
Save External Bucket
to save the settings.
Changing the backup schedule from the default schedule {#gcp-changing-the-backup-schedule}
External Backups will now happen in your bucket on the default schedule.
Alternatively, you can configure the backup schedule from the
Settings
page.
If configured differently, the custom schedule is used to write backups to your
bucket and the default schedule (backups every 24 hours) is used for backups in
ClickHouse cloud owned bucket.
View backups stored in your bucket {#gcp-view-backups-stored-in-your-bucket}
The Backups page should display these backups in your bucket in a separate table as shown below:
Restoring backups from GCP {#gcp-restoring-backups-from-gcp}
Follow the steps below to restore backups from GCP:
Create a new service to restore to {#gcp-create-new-service-to-restore-to}
Create a new service to restore the backup to.
Get SQL command used to restore backup {#gcp-obtain-sql-command-to-restore-backup}
Click on the
access or restore a backup
link above the list of backups in the
UI to get the SQL command to restore the backup. The command should look like this,
and you can pick the appropriate backup from the dropdown to get the restore
command for that specific backup. You will need to add your secret access key
to the command:
:::warning Moving backups to another location
If you move the backups to another location, you will need to customize the restore command to reference the new location.
:::
:::tip ASYNC command
For the Restore command you can also optionally add an
ASYNC
command at the end for large restores.
This allows the restores to happen asynchronously, so that if connection is lost, the restore keeps running.
It is important to note that the ASYNC command immediately returns a status of success.
This does not mean the restore was successful.
You will need to monitor the
system.backups
table to see if the restore has finished and if it succeeded or failed.
:::
Run SQL command to restore backup {#gcp-run-sql-command-to-restore-backup}
Run the restore command from the SQL console in the newly created service to
restore the backup.
Azure {#azure}
Taking backups to Azure {#taking-backups-to-azure}
Follow the steps below to take backups to Azure:
Steps to follow in Azure {#steps-to-follow-in-azure}
Create a storage account {#azure-create-a-storage-account}
Create a storage account or select an existing storage account in the Azure
portal where you want to store your backups.
Get connection string {#azure-get-connection-string}
a. In your storage account overview, look for the section called
Security + networking
and click on
Access keys
.
b. Here, you will see
key1
and
key2
. Under each key, you’ll find a
Connection string
field. | {"source_file": "02_backup_restore_from_ui.md"} | [
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0.042666245251894,
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0.06655307114124298,
-0.0427783764898777,
-0.003537180135026574,
0.07020886242389679,
-0.02... |
cf5066db-2492-4a5c-aaa8-dd6d54c23c17 | b. Here, you will see
key1
and
key2
. Under each key, you’ll find a
Connection string
field.
c. Click
Show
to reveal the connection string. Copy the connection string which you will use to for set-up on ClickHouse Cloud.
Steps to follow in ClickHouse Cloud {#azure-cloud-steps}
Follow the steps below in the ClickHouse Cloud console to configure the external bucket:
Change external backup {#azure-configure-external-bucket}
On the
Settings
page, click on
Change external backup
Provide connection string and container name for your Azure storage account {#azure-provide-connection-string-and-container-name-azure}
On the next screen provide the Connection String and Container Name for your
Azure storage account created in the previous section:
Save external bucket {#azure-save-external-bucket}
Click on
Save External Bucket
to save the settings
Changing the backup schedule from the default schedule {#azure-changing-the-backup-schedule}
External Backups will now happen in your bucket on the default schedule. Alternatively,
you can configure the backup schedule from the “Settings” page. If configured differently,
the custom schedule is used to write backups to your bucket and the default schedule
(backups every 24 hours) is used for backups in ClickHouse cloud owned bucket.
View backups stored in your bucket {#azure-view-backups-stored-in-your-bucket}
The Backups page should display these backups in your bucket in a separate table
as shown below:
Restoring backups from Azure {#azure-restore-steps}
To restore backups from Azure, follow the steps below:
Create a new service to restore to {#azure-create-new-service-to-restore-to}
Create a new service to restore the backup to. Currently, we only support
restoring a backup into a new service.
Get SQL command used to restore backup {#azure-obtain-sql-command-to-restore-backup}
Click on the
access or restore a backup
link above the list of backups in the
UI to obtain the SQL command to restore the backup. The command should look like
this, and you can pick the appropriate backup from the dropdown to get the
restore command for that specific backup. You will need to add your Azure
storage account connection string to the command.
:::warning Moving backups to another location
If you move the backups to another location, you will need to customize the restore command to reference the new location.
:::
:::tip ASYNC command
For the Restore command you can also optionally add an
ASYNC
command at the end for large restores.
This allows the restores to happen asynchronously, so that if connection is lost, the restore keeps running.
It is important to note that the ASYNC command immediately returns a status of success.
This does not mean the restore was successful.
You will need to monitor the
system.backups
table to see if the restore has finished and if it succeeded or failed.
::: | {"source_file": "02_backup_restore_from_ui.md"} | [
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-0.00... |
9f4df55c-b30e-4b4f-8246-cf2ef0d115f8 | Run SQL command to restore backup {#azure-run-sql-command-to-restore-backup}
Run the restore command from the SQL console in the newly created service to
restore the backup. | {"source_file": "02_backup_restore_from_ui.md"} | [
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0.04072... |
cc5e8716-e612-4651-b165-a0a6f530aa7b | sidebar_label: 'Console audit log events'
slug: /cloud/security/audit-logging
title: 'Console audit log events'
description: 'This page describes the events that are recorded to the console audit log.'
doc_type: 'reference'
keywords: ['audit logging', 'security', 'compliance', 'logs', 'monitoring']
Console audit log events {#console-audit-log-events}
The different types of events captured for the organization are grouped in 3 categories:
Organization
,
Service
and
User
. For more information about the audit log and how to export or add an API integration, review the
console audit log
documentation in the Guides section above.
The following events are recorded to the audit log.
Organization {#organization}
Organization created
Organization deleted
Organization name changed
Service {#service}
Service created
Service deleted
Service stopped
Service started
Service name changed
Service IP access list changed
Service password reset
User {#user}
User role changed
User removed from organization
User invited to organization
User joined organization
User invitation deleted
User left organization | {"source_file": "02_audit-logging.md"} | [
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2d3435f5-85da-4d21-9c32-297bf73df63e | sidebar_label: 'Console roles and permissions'
slug: /cloud/security/console-roles
title: 'Console roles and permissions'
description: 'This page describes the standard roles and associated permissions in ClickHouse Cloud console'
doc_type: 'reference'
keywords: ['console roles', 'permissions', 'access control', 'security', 'rbac']
Organization roles {#organization-roles}
Refer to
Manage cloud users
for instructions on assigning organization roles.
ClickHouse has four organization level roles available for user management. Only the admin role has default access to services. All other roles must be combined with service level roles to interact with services.
| Role | Description |
|-----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Admin | Perform all administrative activities for an organization and control all settings. This role is assigned to the first user in the organization by default and automatically has Service Admin permissions on all services. |
| Developer | View access to the organization and ability to generate API keys with the same or lower permissions. |
| Billing | View usage and invoices, and manage payment methods. |
| Member | Sign-in only with the ability to manage personal profile settings. Assigned to SAML SSO users by default. |
Service roles {#service-roles}
Refer to
Manage cloud users
for instructions on assigning service roles.
Service permissions must be explicitly granted by an admin to users with roles other than admin. Service Admin is pre-configured with SQL console admin access, but may be modified to reduce or remove permissions.
| Role | Description |
|-------------------|-----------------------------|
| Service read only | View services and settings. |
| Service admin | Manage service settings. |
SQL console roles {#sql-console-roles}
Refer to
Manage SQL console role assignments
for instructions on assigning SQL console roles. | {"source_file": "01_console-roles.md"} | [
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541af7b6-e02a-45d0-a1e2-b88d29c01489 | SQL console roles {#sql-console-roles}
Refer to
Manage SQL console role assignments
for instructions on assigning SQL console roles.
| Role | Description |
|-----------------------|------------------------------------------------------------------------------------------------|
| SQL console read only | Read only access to databases within the service. |
| SQL console admin | Administrative access to databases within the service equivalent to the Default database role. | | {"source_file": "01_console-roles.md"} | [
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841fd5e3-8f4b-41c3-9987-81d65484e616 | title: 'Compliance overview'
slug: /cloud/security/compliance-overview
description: 'Overview of ClickHouse Cloud security and compliance certifications including SOC 2, ISO 27001, U.S. DPF, and HIPAA'
doc_type: 'reference'
keywords: ['ClickHouse Cloud', 'SOC 2 Type II', 'ISO 27001', 'HIPAA', 'U.S. DPF', 'PCI']
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Security and compliance reports
ClickHouse evaluates the security and compliance needs of our customers and is continuously expanding the program as additional reports are requested. For additional information or to download the reports visit our
Trust Center
.
SOC 2 Type II (since 2022) {#soc-2-type-ii-since-2022}
System and Organization Controls (SOC) 2 is a report focusing on security, availability, confidentiality, processing integrity and privacy criteria contained in the Trust Services Criteria (TSC) as applied to an organization's systems and is designed to provide assurance about these controls to relying parties (our customers). ClickHouse works with independent external auditors to undergo an audit at least once per year addressing security, availability and processing integrity of our systems and confidentiality and privacy of the data processed by our systems. The report addresses both our ClickHouse Cloud and Bring Your Own Cloud (BYOC) offerings.
ISO 27001 (Since 2023) {#iso-27001-since-2023}
International Standards Organization (ISO) 27001 is an international standard for information security. It requires companies to implement an Information Security Management System (ISMS) that includes processes for managing risks, creating and communicating policies, implementing security controls, and monitoring to ensure components remain relevant and effective. ClickHouse conducts internal audits and works with independent external auditors to undergo audits and interim inspections for the 2 years between certificate issuance.
U.S. DPF (since 2024) {#us-dpf-since-2024}
The U.S. Data Privacy Framework was developed to provide U.S. organizations with reliable mechanisms for personal data transfers to the United States from the European Union/ European Economic Area, the United Kingdom, and Switzerland that are consistent with EU, UK and Swiss law (https://dataprivacyframework.gov/Program-Overview). ClickHouse self-certified to the framework and is listed on the
Data Privacy Framework List
.
HIPAA (since 2024) {#hipaa-since-2024} | {"source_file": "03_compliance-overview.md"} | [
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ea09858c-3d1f-4ae9-974b-869e0885e2a6 | HIPAA (since 2024) {#hipaa-since-2024}
The Health Insurance Portability and Accountability Act (HIPAA) of 1996 is a United States based privacy law focused on management of protected health information (PHI). HIPAA has several requirements, including the
Security Rule
, which is focused on protecting electronic personal health information (ePHI). ClickHouse has implemented administrative, physical and technical safeguards to ensure the confidentiality, integrity and security of ePHI stored in designated services. These activities are incorporated in our SOC 2 Type II report available for download in our
Trust Center
.
Refer to
HIPAA onboarding
for steps to complete a Business Associate Agreement (BAA) and deploy HIPAA compliant services.
PCI service provider (since 2025) {#pci-service-provider-since-2025}
The
Payment Card Industry Data Security Standard (PCI DSS)
is a set of rules created by the PCI Security Standards Council to protect credit card payment data. ClickHouse has undergone an external audit with a Qualified Security Assessor (QSA) that resulted in a passing Report on Compliance (ROC) against PCI criteria relevant to storing credit card data. To download a copy of our Attestation on Compliance (AOC) and PCI responsibility overview, please visit our
Trust Center
.
Refer to
PCI onboarding
for steps to deploy PCI compliant services.
Privacy compliance {#privacy-compliance}
In addition to the items above, ClickHouse maintains internal compliance programs addressing the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA) and other relevant privacy frameworks.
Payment compliance {#payment-compliance}
ClickHouse provides a secure method to pay by credit card that is compliant with
PCI SAQ A v4.0
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19da1049-f601-4d93-bad6-9af8a0b18b1b | slug: /cloud/reference/changelogs
title: 'Changelogs'
description: 'Landing page for Cloud changelogs'
doc_type: 'landing-page'
keywords: ['ClickHouse Cloud changelog', 'Cloud release notes', 'cloud updates', 'version history']
| Page | Description |
|---------------------------------------------------------------|-------------------------------------------------|
|
Cloud Changelog
| Changelog for ClickHouse Cloud |
|
Release Notes
| Release notes for all ClickHouse Cloud releases | | {"source_file": "index.md"} | [
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e996d270-9681-48ea-8218-6f72d7405ede | slug: /whats-new/cloud
sidebar_label: 'Cloud changelog'
title: 'Cloud Changelog'
description: 'ClickHouse Cloud changelog providing descriptions of what is new in each ClickHouse Cloud release'
doc_type: 'changelog'
keywords: ['changelog', 'release notes', 'updates', 'new features', 'cloud changes']
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import prometheus from '@site/static/images/cloud/reference/june-28-prometheus.png';
import kafka_config from '@site/static/images/cloud/reference/june-13-kafka-config.png';
import fast_releases from '@site/static/images/cloud/reference/june-13-fast-releases.png';
import share_queries from '@site/static/images/cloud/reference/may-30-share-queries.png';
import query_endpoints from '@site/static/images/cloud/reference/may-17-query-endpoints.png';
import dashboards from '@site/static/images/cloud/reference/may-30-dashboards.png';
In addition to this ClickHouse Cloud changelog, please see the
Cloud Compatibility
page.
:::tip[Automatically keep up to date!]
Subscribe to Cloud Changelog via RSS
:::
November 7, 2025 {#november-7-2025}
ClickHouse Cloud console now supports configuring replica sizes in increments of 1 vCPU, 4 GiB from the cloud console.
These options are available both when setting up a new service as well as when setting minimum and maximum replica sizes on the settings page.
Custom hardware profiles (available on the Enterprise tier) now support idling. | {"source_file": "01_changelog.md"} | [
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0.091046042740345,
0.0673210620880127,
-0.028237376362085342,
0.04254678264260292,
-0.00965... |
0e55a9b2-b0f2-43b0-86c9-09ef1c2c54fc | Custom hardware profiles (available on the Enterprise tier) now support idling.
ClickHouse Cloud now offers a simplified purchasing experience through AWS Marketplace, with separate options for
pay-as-you-go
and
committed spend contracts
.
Alerting is now available for ClickStack users in ClickHouse Cloud.
Users can now create and manage alerts directly in the HyperDX UI, across logs, metrics, and traces with no extra setup, no extra infra or service, and no config. Alerts integrate with Slack, PagerDuty, and more.
For more information see the
alerting documentation
.
October 17, 2025 {#october-17-2025}
Service Monitoring - Resource Utilization Dashboard
The CPU utilization and memory utilization metrics display will change to show the maximum utilization metric during a particular time period to better surface instances of underprovisionment, from average.
In addition, the CPU utilization metric will show a kubernetes-level CPU utilization metric which more closely resembles the metric used by ClickHouse Cloud’s autoscaler.
External Buckets
ClickHouse Cloud now lets you export backups directly to your own cloud service provider account.
Connect your external storage bucket - AWS S3, Google Cloud Storage, or Azure Blob Storage - and take control of your backup management.
August 29, 2025 {#august-29-2025}
ClickHouse Cloud Azure Private Link
has switched from using Resource GUID to Resource ID filters for resource identification. You can still use the legacy Resource GUID, which is backward compatible, but we recommend switching to Resource ID filters. For migration details see the
docs
for Azure Private Link.
August 22, 2025 {#august-22-2025}
ClickHouse Connector for AWS Glue
You can now use the official
ClickHouse Connector for AWS Glue
that is available from the
AWS Marketplace
. Utilizes AWS Glue’s Apache
Spark-based serverless engine for extracting, transforming and loading data integration between ClickHouse and other data sources. Get
started by following along with the announcement
blogpost
for how to create tables, write and read data between ClickHouse and Spark.
Change to the minimum number of replicas in a service
Services which have been scaled up can now be
scaled back down
to use a single replica (previously the minimum was 2 replicas). Note: single replica services have reduced availability and are not recommended for production usage.
ClickHouse Cloud will begin to send notifications related to service scaling and service version upgrades, by default for administrator roles. Users can adjust their notification preferences in their notification settings.
August 13, 2025 {#august-13-2025}
ClickPipes for MongoDB CDC now in Private Preview | {"source_file": "01_changelog.md"} | [
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0.047004275023937225,
... |
de342ecd-8185-4dda-997b-c11beddd3fa6 | August 13, 2025 {#august-13-2025}
ClickPipes for MongoDB CDC now in Private Preview
You can now use ClickPipes to replicate data from MongoDB into ClickHouse Cloud in a few clicks, enabling
real-time analytics without the need for external ETL tools. The connector supports continuous
replication as well as one-time migrations, and is compatible with MongoDB Atlas and self-hosted MongoDB
deployments. Read the
blogpost
for an overview of the MongoDB CDC connector and
sign up for early access here
!
August 8, 2025 {#august-08-2025}
Notifications
: Users will now receive a UI notification when their service starts upgrading to a new ClickHouse version. Additional Email and Slack notifications can be added via the notification center.
ClickPipes
: Azure Blob Storage (ABS) ClickPipes support was added to the ClickHouse Terraform provider. See the provider documentation for an example of how to programmatically create an ABS ClickPipe.
[Bug fix] Object storage ClickPipes writing to a destination table using the Null engine now report "Total records" and "Data ingested" metrics in the UI.
[Bug fix] The “Time period” selector for metrics in the UI defaulted to “24 hours” regardless of the selected time period. This has now been fixed, and the UI correctly updates the charts for the selected time period.
Cross-region private link (AWS)
is now Generally Available. Please refer to the
documentation
for the list of supported regions.
July 31, 2025 {#july-31-2025}
Vertical scaling for ClickPipes now available
Vertical scaling is now available for streaming ClickPipes
.
This feature allows you to control the size of each replica, in addition to the
number of replicas (horizontal scaling). The details page for each ClickPipe now
also includes per-replica CPU and memory utilization, which helps you better
understand your workloads and plan re-sizing operations with confidence.
July 24, 2025 {#july-24-2025}
ClickPipes for MySQL CDC now in public beta
The MySQL CDC connector in ClickPipes is now widely available in public beta. With just a few clicks,
you can start replicating your MySQL (or MariaDB) data directly into ClickHouse Cloud in real-time,
with no external dependencies. Read the
blogpost
for an overview of the connector and follow the
quickstart
to get up and running.
July 11, 2025 {#june-11-2025}
New services now store database and table metadata in a central
SharedCatalog
,
a new model for coordination and object lifecycles which enables:
Cloud-scale DDL
, even under high concurrency
Resilient deletion and new DDL operations
Fast spin-up and wake-ups
as stateless nodes now launch with no disk dependencies
Stateless compute across both native and open formats
, including Iceberg and Delta Lake
Read more about SharedCatalog in our
blog
We now support the ability to launch HIPAA compliant services in GCP
europe-west4
June 27, 2025 {#june-27-2025} | {"source_file": "01_changelog.md"} | [
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0.014996900223195553,
0.03000... |
ca1fa9a8-26ba-4fe2-9420-dd9f684e8179 | Read more about SharedCatalog in our
blog
We now support the ability to launch HIPAA compliant services in GCP
europe-west4
June 27, 2025 {#june-27-2025}
We now officially support a Terraform provider for managing database privileges
which is also compatible with self-managed deployments. Please refer to the
blog
and our
docs
for more information.
Enterprise tier services can now enlist in the
slow release channel
to defer
upgrades by two weeks after the regular release to permit additional time for
testing.
June 13, 2025 {#june-13-2025}
We're excited to announce that ClickHouse Cloud Dashboards are now generally available. Dashboards allow users to visualize queries on dashboards, interact with data via filters and query parameters, and manage sharing.
API key IP filters: we are introducing an additional layer of protection for your interactions with ClickHouse Cloud. When generating an API key, you may setup an IP allow list to limit where the API key may be used. Please refer to the
documentation
for details.
May 30, 2025 {#may-30-2025}
We're excited to announce general availability of
ClickPipes for Postgres CDC
in ClickHouse Cloud. With just a few clicks, you can now replicate your Postgres
databases and unlock blazing-fast, real-time analytics. The connector delivers
faster data synchronization, latency as low as a few seconds, automatic schema changes,
fully secure connectivity, and more. Refer to the
blog
for
more information. To get started, refer to the instructions
here
.
Introduced new improvements to the SQL console dashboards:
Sharing: You can share your dashboard with your team members. Four levels of access are supported, that can be adjusted both globally and on a per-user basis:
Write access
: Add/edit visualizations, refresh settings, interact with dashboards via filters.
Owner
: Share a dashboard, delete a dashboard, and all other permissions of a user with "write access".
Read-only access
: View and interact with dashboard via filters
No access
: Cannot view a dashboard
For existing dashboards that have already been created, Organization Administrators can assign existing dashboards to themselves as owners.
You can now add a table or chart from the SQL console to a dashboard from the query view.
We are enlisting preview participants for
Distributed cache
for AWS and GCP. Read more in the
blog
.
May 16, 2025 {#may-16-2025}
Introduced the Resource Utilization Dashboard which provides a view of
resources being used by a service in ClickHouse Cloud. The following metrics
are scraped from system tables, and displayed on this dashboard:
Memory & CPU: Graphs for
CGroupMemoryTotal
(Allocated Memory),
CGroupMaxCPU
(allocated CPU),
MemoryResident
(memory used), and
ProfileEvent_OSCPUVirtualTimeMicroseconds
(CPU used) | {"source_file": "01_changelog.md"} | [
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0.02108404040336609,
-0.... |
33b2eb62-2536-4c98-82f1-3a92f02ccec9 | Memory & CPU: Graphs for
CGroupMemoryTotal
(Allocated Memory),
CGroupMaxCPU
(allocated CPU),
MemoryResident
(memory used), and
ProfileEvent_OSCPUVirtualTimeMicroseconds
(CPU used)
Data Transfer: Graphs showing data ingress and egress from ClickHouse Cloud. Learn more
here
.
We're excited to announce the launch of our new ClickHouse Cloud Prometheus/Grafana mix-in,
built to simplify monitoring for your ClickHouse Cloud services.
This mix-in uses our Prometheus-compatible API endpoint to seamlessly integrate
ClickHouse metrics into your existing Prometheus and Grafana setup. It includes
a pre-configured dashboard that gives you real-time visibility into the health
and performance of your services. Refer to the launch
blog
to read more.
April 18, 2025 {#april-18-2025}
Introduced a new
Member
organization level role and two new service level
roles:
Service Admin
and
Service Read Only
.
Member
is an organization level role that is assigned to SAML SSO users by
default and provides only sign-in and profile update capabilities.
Service Admin
and
Service Read Only
roles for one or more services can be assigned to users
with
Member
,
Developer
, or
Billing Admin
roles. For more information
see
"Access control in ClickHouse Cloud"
ClickHouse Cloud now offers
HIPAA
and
PCI
services in the following regions
for
Enterprise
customers: AWS eu-central-1, AWS eu-west-2, AWS us-east-2.
Introduced
user facing notifications for ClickPipes
. This feature sends
automatic alerts for ClickPipes failures via email, ClickHouse Cloud UI, and
Slack. Notifications via email and UI are enabled by default and can be
configured per pipe. For
Postgres CDC ClickPipes
, alerts also cover
replication slot threshold (configurable in the
Settings
tab), specific error
types, and self-serve steps to resolve failures.
MySQL CDC private preview
is now open. This lets customers replicate MySQL
databases to ClickHouse Cloud in a few clicks, enabling fast analytics and
removing the need for external ETL tools. The connector supports both continuous
replication and one-time migrations, whether MySQL is on the cloud (RDS,
Aurora, Cloud SQL, Azure, etc.) or on-premises. You can sign up to the private
preview by
following this link
.
Introduced
AWS PrivateLink for ClickPipes
. You can use AWS PrivateLink to
establish secure connectivity between VPCs, AWS services, your on-premises
systems, and ClickHouse Cloud. This can be done without exposing traffic to
the public internet while moving data from sources like Postgres, MySQL, and
MSK on AWS. It also supports cross-region access through VPC service endpoints.
PrivateLink connectivity set-up is now
fully self-serve
through ClickPipes.
April 4, 2025 {#april-4-2025} | {"source_file": "01_changelog.md"} | [
-0.05961372330784798,
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-0.03090333752334118,
0.013814004138112068,
-... |
4e59cb44-d576-47c6-8ce9-66e010f10f80 | through ClickPipes.
April 4, 2025 {#april-4-2025}
Slack notifications for ClickHouse Cloud: ClickHouse Cloud now supports Slack notifications for billing, scaling, and ClickPipes events, in addition to in-console and email notifications. These notifications are sent via the ClickHouse Cloud Slack application. Organization admins can configure these notifications via the notification center by specifying slack channels to which notifications should be sent.
Users running Production and Development services will now see ClickPipes and data transfer usage price on their bills.
March 21, 2025 {#march-21-2025}
Cross-region Private Link connectivity on AWS is now in Beta. Please refer to
ClickHouse Cloud private link
docs
for
details of how to set up and list of supported regions.
The maximum replica size available for services on AWS is now set to 236 GiB RAM.
This allows for efficient utilization, while ensuring we have resources
allocated to background processes.
March 7, 2025 {#march-7-2025}
New
UsageCost
API endpoint: The API specification now supports a new endpoint
for retrieving usage information. This is an organization endpoint and usage
costs can be queried for a maximum of 31 days. The metrics that can be
retrieved include Storage, Compute, Data Transfer and ClickPipes. Please refer
to the
documentation
for details.
Terraform provider
v2.1.0
release supports enabling the MySQL endpoint.
February 21, 2025 {#february-21-2025}
ClickHouse Bring Your Own Cloud (BYOC) for AWS is now generally available {#clickhouse-byoc-for-aws-ga}
In this deployment model, data plane components (compute, storage, backups, logs, metrics)
run in the Customer VPC, while the control plane (web access, APIs, and billing)
remains within the ClickHouse VPC. This setup is ideal for large workloads that
need to comply with strict data residency requirements by ensuring all data stays
within a secure customer environment.
For more details, you can refer to the
documentation
for BYOC
or read our
announcement blog post
.
Contact us
to request access.
Postgres CDC connector for ClickPipes {#postgres-cdc-connector-for-clickpipes}
Postgres CDC connector for ClickPipes allows users to seamlessly replicate their Postgres databases to ClickHouse Cloud.
To get started, refer to the
documentation
for ClickPipes Postgres CDC connector.
For more information on customer use cases and features, please refer to the
landing page
and the
launch blog
.
PCI compliance for ClickHouse Cloud on AWS {#pci-compliance-for-clickhouse-cloud-on-aws}
ClickHouse Cloud now supports
PCI-compliant services
for
Enterprise tier
customers in
us-east-1
and
us-west-2
regions. Users who wish to launch
a service in a PCI-compliant environment can contact
support
for assistance.
Transparent Data Encryption and Customer Managed Encryption Keys on Google Cloud Platform {#tde-and-cmek-on-gcp} | {"source_file": "01_changelog.md"} | [
-0.004309096373617649,
-0.06906653195619583,
-0.018451351672410965,
-0.00979964155703783,
0.014316917397081852,
-0.007068469189107418,
-0.007101908326148987,
0.0053175524808466434,
0.018634602427482605,
0.06589581817388535,
-0.020866408944129944,
0.006446042098104954,
-0.007333237677812576,
... |
cf869ba1-bec1-43e3-9565-228842c36191 | for assistance.
Transparent Data Encryption and Customer Managed Encryption Keys on Google Cloud Platform {#tde-and-cmek-on-gcp}
Support for
Transparent Data Encryption (TDE)
and
Customer Managed
Encryption Keys (CMEK)
is now available for ClickHouse Cloud on
Google Cloud Platform (GCP)
.
Please refer to the
documentation
of these features for more information.
AWS Middle East (UAE) availability {#aws-middle-east-uae-availability}
New region support is added for ClickHouse Cloud, which is now available in the
AWS Middle East (UAE) me-central-1
region.
ClickHouse Cloud guardrails {#clickhouse-cloud-guardrails}
To promote best practices and ensure stable use of ClickHouse Cloud, we are
introducing guardrails for the number of tables, databases, partitions and parts
in use.
Refer to the
usage limits
section of the documentation for details.
If your service is already above these limits, we will permit a 10% increase.
Please contact
support
if you have any questions.
January 27, 2025 {#january-27-2025}
Changes to ClickHouse Cloud tiers {#changes-to-clickhouse-cloud-tiers}
We are dedicated to adapting our products to meet the ever-changing requirements of our customers. Since its introduction in GA over the past two years, ClickHouse Cloud has evolved substantially, and we've gained invaluable insights into how our customers leverage our cloud offerings.
We are introducing new features to optimize the sizing and cost-efficiency of ClickHouse Cloud services for your workloads. These include
compute-compute separation
, high-performance machine types, and
single-replica services
. We are also evolving automatic scaling and managed upgrades to execute in a more seamless and reactive fashion.
We are adding a
new Enterprise tier
to serve the needs of the most demanding customers and workloads, with focus on industry-specific security and compliance features, even more controls over underlying hardware and upgrades, and advanced disaster recovery features.
To support these changes, we are restructuring our current
Development
and
Production
tiers to more closely match how our evolving customer base is using our offerings. We are introducing the
Basic
tier, oriented toward users that are testing out new ideas and projects, and the
Scale
tier, matching users working with production workloads and data at scale.
You can read about these and other functional changes in this
blog
. Existing customers will need to take action to select a
new plan
. Customer-facing communication was sent via email to organization administrators.
Warehouses: Compute-compute separation (GA) {#warehouses-compute-compute-separation-ga}
Compute-compute separation (also known as "Warehouses") is Generally Available; please refer to
blog
for more details and the
documentation
.
Single-replica services {#single-replica-services} | {"source_file": "01_changelog.md"} | [
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-0.06153924763202667,
0.06773117929697037,
-0.049395520240068436,
0.004069819115102291,
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0.057713426649570465,
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0.06423445045948029,
0.004297178704291582,
-0.012203121557831764,
0.08451021462678909,
-0.0... |
8610afed-11ff-4957-8120-e0c076cd2821 | Compute-compute separation (also known as "Warehouses") is Generally Available; please refer to
blog
for more details and the
documentation
.
Single-replica services {#single-replica-services}
We are introducing the concept of a "single-replica service", both as a standalone offering and within warehouses. As a standalone offering, single-replica services are size limited and intended to be used for small test workloads. Within warehouses, single-replica services can be deployed at larger sizes, and utilized for workloads not requiring high availability at scale, such as restartable ETL jobs.
Vertical auto-scaling improvements {#vertical-auto-scaling-improvements}
We are introducing a new vertical scaling mechanism for compute replicas, which we call "Make Before Break" (MBB). This approach adds one or more replicas of the new size before removing the old replicas, preventing any loss of capacity during scaling operations. By eliminating the gap between removing existing replicas and adding new ones, MBB creates a more seamless and less disruptive scaling process. It is especially beneficial in scale-up scenarios, where high resource utilization triggers the need for additional capacity, since removing replicas prematurely would only exacerbate the resource constraints.
Horizontal scaling (GA) {#horizontal-scaling-ga}
Horizontal scaling is now Generally Available. Users can add additional replicas to scale out their service through the APIs and the cloud console. Please refer to the
documentation
for information.
Configurable backups {#configurable-backups}
We now support the ability for customers to export backups to their own cloud account; please refer to the
documentation
for additional information.
Managed upgrade improvements {#managed-upgrade-improvements}
Safe managed upgrades deliver significant value to our users by allowing them to stay current with the database as it moves forward to add features. With this rollout, we applied the "make before break" (or MBB) approach to upgrades, further reducing impact to running workloads.
HIPAA support {#hipaa-support}
We now support HIPAA in compliant regions, including AWS
us-east-1
,
us-west-2
and GCP
us-central1
,
us-east1
. Customers wishing to onboard must sign a Business Associate Agreement (BAA) and deploy to the compliant version of the region. For more information on HIPAA, please refer to the
documentation
.
Scheduled upgrades {#scheduled-upgrades}
Users can schedule upgrades for their services. This feature is supported for Enterprise tier services only. For more information on Scheduled upgrades, please refer to the
documentation
.
Language client support for complex types {#language-client-support-for-complex-types}
Golang
,
Python
, and
NodeJS
clients added support for Dynamic, Variant, and JSON types.
DBT support for refreshable materialized views {#dbt-support-for-refreshable-materialized-views} | {"source_file": "01_changelog.md"} | [
-0.08119422197341919,
0.02197713777422905,
0.013821209780871868,
0.0011926227016374469,
-0.028174616396427155,
-0.06209170073270798,
-0.11568723618984222,
-0.034249089658260345,
0.002759222174063325,
0.04051559045910835,
-0.044782962650060654,
0.004871053621172905,
0.05547359958291054,
-0.... |
0781b797-73db-46fd-b764-6623ff43881d | Golang
,
Python
, and
NodeJS
clients added support for Dynamic, Variant, and JSON types.
DBT support for refreshable materialized views {#dbt-support-for-refreshable-materialized-views}
DBT now
supports Refreshable Materialized Views
in the
1.8.7
release.
JWT token support {#jwt-token-support}
Support has been added for JWT-based authentication in the JDBC driver v2, clickhouse-java,
Python
, and
NodeJS
clients.
JDBC / Java will be in
0.8.0
when it's released - ETA pending.
Prometheus integration improvements {#prometheus-integration-improvements}
We've added several enhancements for the Prometheus integration:
Organization-level endpoint
. We've introduced an enhancement to our Prometheus integration for ClickHouse Cloud. In addition to service-level metrics, the API now includes an endpoint for
organization-level metrics
. This new endpoint automatically collects metrics for all services within your organization, streamlining the process of exporting metrics into your Prometheus collector. These metrics can be integrated with visualization tools like Grafana and Datadog for a more comprehensive view of your organization's performance.
This feature is available now for all users. You can find more details
here
.
Filtered metrics
. We've added support for returning a filtered list of metrics in our Prometheus integration for ClickHouse Cloud. This feature helps reduce response payload size by enabling you to focus on metrics that are critical for monitoring the health of your service.
This functionality is available via an optional query parameter in the API, making it easier to optimize your data collection and streamline integrations with tools like Grafana and Datadog.
The filtered metrics feature is now available for all users. You can find more details
here
.
December 20, 2024 {#december-20-2024}
Marketplace subscription organization attachment {#marketplace-subscription-organization-attachment}
You can now attach your new marketplace subscription to an existing ClickHouse Cloud organization. Once you finish subscribing to the marketplace and redirect to ClickHouse Cloud, you can connect an existing organization created in the past to the new marketplace subscription. From this point, your resources in the organization will be billed via the marketplace.
Force OpenAPI key expiration {#force-openapi-key-expiration}
It is now possible to restrict the expiry options of API keys so you don't create unexpired OpenAPI keys. Please contact the ClickHouse Cloud Support team to enable these restrictions for your organization.
Custom emails for notifications {#custom-emails-for-notifications} | {"source_file": "01_changelog.md"} | [
-0.1396017223596573,
-0.02060968428850174,
0.018743285909295082,
0.006444974336773157,
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-0.03199021890759468,
0.03030342236161232,
-0.0358525887131691,
-0.03331997990608215,
-0.06113215535879135,
-0.00006961079634493217,
0.013862538151443005,
0.0... |
8bcd65ab-2696-48d1-8421-93361923dc7d | Custom emails for notifications {#custom-emails-for-notifications}
Org Admins can now add more email addresses to a specific notification as additional recipients. This is useful in case you want to send notifications to an alias or to other users within your organization who might not be users of ClickHouse Cloud. To configure this, go to the Notification Settings from the cloud console and edit the email addresses that you want to receive the email notifications.
December 6, 2024 {#december-6-2024}
BYOC (beta) {#byoc-beta}
Bring Your Own Cloud for AWS is now available in Beta. This deployment model allows you to deploy and run ClickHouse Cloud in your own AWS account. We support deployments in 11+ AWS regions, with more coming soon. Please
contact support
for access. Note that this deployment is reserved for large-scale deployments.
Postgres Change Data Capture (CDC) connector in ClickPipes {#postgres-change-data-capture-cdc-connector-in-clickpipes}
This turnkey integration enables customers to replicate their Postgres databases to ClickHouse Cloud in just a few clicks and leverage ClickHouse for blazing-fast analytics. You can use this connector for both continuous replication and one-time migrations from Postgres.
Dashboards (beta) {#dashboards-beta}
This week, we're excited to announce the Beta launch of Dashboards in ClickHouse Cloud. With Dashboards, users can turn saved queries into visualizations, organize visualizations onto dashboards, and interact with dashboards using query parameters. To get started, follow the
dashboards documentation
.
Query API endpoints (GA) {#query-api-endpoints-ga}
We are excited to announce the GA release of Query API Endpoints in ClickHouse Cloud. Query API Endpoints allow you to spin up RESTful API endpoints for saved queries in just a couple of clicks and begin consuming data in your application without wrangling language clients or authentication complexity. Since the initial launch, we have shipped a number of improvements, including:
Reducing endpoint latency, especially for cold-starts
Increased endpoint RBAC controls
Configurable CORS-allowed domains
Result streaming
Support for all ClickHouse-compatible output formats
In addition to these improvements, we are excited to announce generic query API endpoints that, leveraging our existing framework, allow you to execute arbitrary SQL queries against your ClickHouse Cloud service(s). Generic endpoints can be enabled and configured from the service settings page.
To get started, follow the
Query API Endpoints documentation
.
Native JSON support (Beta) {#native-json-support-beta}
We are launching Beta for our native JSON support in ClickHouse Cloud. To get started, please get in touch with support
to enable your cloud service
.
Vector search using vector similarity indexes (early access) {#vector-search-using-vector-similarity-indexes-early-access} | {"source_file": "01_changelog.md"} | [
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ede95bab-cf0d-47f9-908d-10e51aee04b9 | Vector search using vector similarity indexes (early access) {#vector-search-using-vector-similarity-indexes-early-access}
We are announcing vector similarity indexes for approximate vector search in early access.
ClickHouse already offers robust support for vector-based use cases, with a wide range of [distance functions]https://clickhouse.com/blog/reinvent-2024-product-announcements#vector-search-using-vector-similarity-indexes-early-access) and the ability to perform linear scans. In addition, more recently, we added an experimental
approximate vector search
approach powered by the
usearch
library and the Hierarchical Navigable Small Worlds (HNSW) approximate nearest neighbor search algorithm.
To get started,
please sign up for the early access waitlist
.
ClickHouse-connect (Python) and ClickHouse Kafka Connect users {#clickhouse-connect-python-and-clickhouse-kafka-connect-users}
Notification emails went out to customers who had experienced issues where the clients could encounter a
MEMORY_LIMIT_EXCEEDED
exception.
Please upgrade to:
- Kafka-Connect: > 1.2.5
- ClickHouse-Connect (Java): > 0.8.6
ClickPipes now supports cross-VPC resource access on AWS {#clickpipes-now-supports-cross-vpc-resource-access-on-aws}
You can now grant uni-directional access to a specific data source like AWS MSK. With Cross-VPC resource access with AWS PrivateLink and VPC Lattice, you can share individual resources across VPC and account boundaries, or even from on-premise networks without compromising on privacy and security when going over a public network. To get started and set up a resource share, you can read the
announcement post
.
ClickPipes now supports IAM for AWS MSK {#clickpipes-now-supports-iam-for-aws-msk}
You can now use IAM authentication to connect to an MSK broker with AWS MSK ClickPipes. To get started, review our
documentation
.
Maximum replica size for new services on AWS {#maximum-replica-size-for-new-services-on-aws}
From now on, any new services created on AWS will allow a maximum available replica size of 236 GiB.
November 22, 2024 {#november-22-2024}
Built-in advanced observability dashboard for ClickHouse Cloud {#built-in-advanced-observability-dashboard-for-clickhouse-cloud}
Previously, the advanced observability dashboard that allows you to monitor ClickHouse server metrics and hardware resource utilization was only available in open-source ClickHouse. We are happy to announce that this feature is now available in the ClickHouse Cloud console.
This dashboard allows you to view queries based on the
system.dashboards
table in an all-in-one UI. Visit
Monitoring > Service Health
page to start using the advanced observability dashboard today.
AI-powered SQL autocomplete {#ai-powered-sql-autocomplete} | {"source_file": "01_changelog.md"} | [
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... |
dae16ce7-2e8e-4b5d-8719-6b8fddebe258 | AI-powered SQL autocomplete {#ai-powered-sql-autocomplete}
We've improved autocomplete significantly, allowing you to get in-line SQL completions as you write your queries with the new AI Copilot. This feature can be enabled by toggling the
"Enable Inline Code Completion"
setting for any ClickHouse Cloud service.
New "billing" role {#new-billing-role}
You can now assign users in your organization to a new
Billing
role that allows them to view and manage billing information without giving them the ability to configure or manage services. Simply invite a new user or edit an existing user's role to assign the
Billing
role.
November 8, 2024 {#november-8-2024}
Customer Notifications in ClickHouse Cloud {#customer-notifications-in-clickhouse-cloud}
ClickHouse Cloud now provides in-console and email notifications for several billing and scaling events. Customers can configure these notifications via the cloud console notification center to only appear on the UI, receive emails, or both. You can configure the category and severity of the notifications you receive at the service level.
In future, we will add notifications for other events, as well as additional ways to receive the notifications.
Please see the
ClickHouse docs
to learn more about how to enable notifications for your service.
October 4, 2024 {#october-4-2024}
ClickHouse Cloud now offers HIPAA-ready services in Beta for GCP {#clickhouse-cloud-now-offers-hipaa-ready-services-in-beta-for-gcp}
Customers looking for increased security for protected health information (PHI) can now onboard to ClickHouse Cloud in
Google Cloud Platform (GCP)
. ClickHouse has implemented administrative, physical and technical safeguards prescribed by the
HIPAA Security Rule
and now has configurable security settings that can be implemented, depending on your specific use case and workload. For more information on available security settings, please review our
Security features page
.
Services are available in GCP
us-central-1
to customers with the
Dedicated
service type and require a Business Associate Agreement (BAA). Contact
sales
or
support
to request access to this feature or join the wait list for additional GCP, AWS, and Azure regions.
Compute-compute separation is now in private preview for GCP and Azure {#compute-compute-separation-is-now-in-private-preview-for-gcp-and-azure}
We recently announced the Private Preview for Compute-Compute Separation for AWS. We're happy to announce that it is now available for GCP and Azure.
Compute-compute separation allows you to designate specific services as read-write or read-only services, allowing you to design the optimal compute configuration for your application to optimize cost and performance. Please
read the docs
for more details.
Self-service MFA recovery codes {#self-service-mfa-recovery-codes} | {"source_file": "01_changelog.md"} | [
-0.0728369951248169,
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0.01... |
2cc915f0-d211-4d66-bfdc-726c3feb3610 | Self-service MFA recovery codes {#self-service-mfa-recovery-codes}
Customers using multi-factor authentication can now obtain recovery codes that can be used in the event of a lost phone or accidentally deleted token. Customers enrolling in MFA for the first time will be provided the code on set up. Customers with existing MFA can obtain a recovery code by removing their existing MFA token and adding a new one.
ClickPipes update: custom certificates, latency insights, and more. {#clickpipes-update-custom-certificates-latency-insights-and-more}
We're excited to share the latest updates for ClickPipes, the easiest way to ingest data into your ClickHouse service. These new features are designed to enhance your control over data ingestion and provide greater visibility into performance metrics.
Custom Authentication Certificates for Kafka
ClickPipes for Kafka now supports custom authentication certificates for Kafka brokers using SASL & public SSL/TLS. You can easily upload your own certificate in the SSL Certificate section during ClickPipe setup, ensuring a more secure connection to Kafka.
Introducing Latency Metrics for Kafka and Kinesis
Performance visibility is crucial. ClickPipes now features a latency graph, giving you insight into the time between message production (whether from a Kafka Topic or a Kinesis Stream) to ingestion in ClickHouse Cloud. With this new metric, you can keep a closer eye on the performance of your data pipelines and optimize accordingly.
Scaling Controls for Kafka and Kinesis (Private Beta)
High throughput can demand extra resources to meet your data volume and latency needs. We're introducing horizontal scaling for ClickPipes, available directly through our cloud console. This feature is currently in private beta, allowing you to scale resources more effectively based on your requirements. Please contact
support
to join the beta.
Raw Message Ingestion for Kafka and Kinesis
It is now possible to ingest an entire Kafka or Kinesis message without parsing it. ClickPipes now offers support for a
_raw_message
virtual column
, allowing users to map the full message into a single String column. This gives you the flexibility to work with raw data as needed.
August 29, 2024 {#august-29-2024}
New Terraform provider version - v1.0.0 {#new-terraform-provider-version---v100}
Terraform allows you to control your ClickHouse Cloud services programmatically, then store your configuration as code. Our Terraform provider has almost 200,000 downloads and is now officially v1.0.0. This new version includes improvements such as better retry logic and a new resource to attach private endpoints to your ClickHouse Cloud service. You can download the
Terraform provider here
and view the
full changelog here
.
2024 SOC 2 Type II report and updated ISO 27001 certificate {#2024-soc-2-type-ii-report-and-updated-iso-27001-certificate} | {"source_file": "01_changelog.md"} | [
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0.004526195582002401,
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0.05032683536410332,
0.003475203411653638,
0.0346621498465538,
-0.0... |
fcda01bf-f5e0-45c3-8905-ac7b5680f03f | 2024 SOC 2 Type II report and updated ISO 27001 certificate {#2024-soc-2-type-ii-report-and-updated-iso-27001-certificate}
We are proud to announce the availability of our 2024 SOC 2 Type II report and updated ISO 27001 certificate, both of which include our recently launched services on Azure as well as continued coverage of services in AWS and GCP.
Our SOC 2 Type II demonstrates our ongoing commitment to achieving security, availability, processing integrity and confidentiality of the services we provide to ClickHouse users. For more information, check out
SOC 2 - SOC for Service Organizations: Trust Services Criteria
issued by the American Institute of Certified Public Accountants (AICPA) and
What is ISO/IEC 27001
from the International Standards Organization (ISO).
Please also check out our
Trust Center
for security and compliance documents and reports.
August 15, 2024 {#august-15-2024}
Compute-compute separation is now in Private Preview for AWS {#compute-compute-separation-is-now-in-private-preview-for-aws}
For existing ClickHouse Cloud services, replicas handle both reads and writes, and there is no way to configure a certain replica to handle only one kind of operation. We have an upcoming new feature called Compute-compute separation that allows you to designate specific services as read-write or read-only services, allowing you to design the optimal compute configuration for your application to optimize cost and performance.
Our new compute-compute separation feature enables you to create multiple compute node groups, each with its own endpoint, that are using the same object storage folder, and thus, with the same tables, views, etc. Read more about
Compute-compute separation here
. Please
contact support
if you would like access to this feature in Private Preview.
ClickPipes for S3 and GCS now in GA, Continuous mode support {#clickpipes-for-s3-and-gcs-now-in-ga-continuous-mode-support}
ClickPipes is the easiest way to ingest data into ClickHouse Cloud. We're happy to announce that
ClickPipes
for S3 and GCS is now
Generally Available
. ClickPipes supports both one-time batch ingest and "continuous mode". An ingest task will load all the files matched by a pattern from a specific remote bucket into the ClickHouse destination table. In "continuous mode", the ClickPipes job will run constantly, ingesting matching files that get added into the remote object storage bucket as they arrive. This will allow users to turn any object storage bucket into a fully fledged staging area for ingesting data into ClickHouse Cloud. Read more about ClickPipes in
our documentation
.
July 18, 2024 {#july-18-2024}
Prometheus endpoint for metrics is now generally available {#prometheus-endpoint-for-metrics-is-now-generally-available} | {"source_file": "01_changelog.md"} | [
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0... |
79d99136-df21-4200-a1d9-a2434952532e | July 18, 2024 {#july-18-2024}
Prometheus endpoint for metrics is now generally available {#prometheus-endpoint-for-metrics-is-now-generally-available}
In our last cloud changelog, we announced the Private Preview for exporting
Prometheus
metrics from ClickHouse Cloud. This feature allows you to use the
ClickHouse Cloud API
to get your metrics into tools like
Grafana
and
Datadog
for visualization. We're happy to announce that this feature is now
Generally Available
. Please see
our docs
to learn more about this feature.
Table inspector in Cloud console {#table-inspector-in-cloud-console}
ClickHouse has commands like
DESCRIBE
that allow you to introspect your table to examine schema. These commands output to the console, but they are often not convenient to use as you need to combine several queries to retrieve all pertinent data about your tables and columns.
We recently launched a
Table Inspector
in the cloud console which allows you to retrieve important table and column information in the UI, without having to write SQL. You can try out the Table Inspector for your services by checking out the cloud console. It provides information about your schema, storage, compression, and more in one unified interface.
New Java Client API {#new-java-client-api}
Our
Java Client
is one of the most popular clients that users use to connect to ClickHouse. We wanted to make it even easier and more intuitive to use, including a re-designed API and various performance optimizations. These changes will make it much easier to connect to ClickHouse from your Java applications. You can read more about how to use the updated Java Client in this
blog post
.
New Analyzer is enabled by default {#new-analyzer-is-enabled-by-default}
For the last couple of years, we've been working on a new analyzer for query analysis and optimization. This analyzer improves query performance and will allow us to make further optimizations, including faster and more efficient
JOIN
s. Previously, it was required that new users enable this feature using the setting
allow_experimental_analyzer
. This improved analyzer is now available on new ClickHouse Cloud services by default.
Stay tuned for more improvements to the analyzer as we have many more optimizations planned.
June 28, 2024 {#june-28-2024}
ClickHouse Cloud for Microsoft Azure is now generally available {#clickhouse-cloud-for-microsoft-azure-is-now-generally-available}
We first announced Microsoft Azure support in Beta
this past May
. In this latest cloud release, we're happy to announce that our Azure support is transitioning from Beta to Generally Available. ClickHouse Cloud is now available on all the three major cloud platforms: AWS, Google Cloud Platform, and now Microsoft Azure. | {"source_file": "01_changelog.md"} | [
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-0... |
a6c4ad4f-eefc-4013-aac9-cf459d390c92 | This release also includes support for subscriptions via the
Microsoft Azure Marketplace
. The service will initially be supported in the following regions:
- United States: West US 3 (Arizona)
- United States: East US 2 (Virginia)
- Europe: Germany West Central (Frankfurt)
If you'd like any specific region to be supported, please
contact us
.
Query log insights {#query-log-insights}
Our new Query Insights UI in the Cloud console makes ClickHouse's built-in query log a lot easier to use. ClickHouse's
system.query_log
table is a key source of information for query optimization, debugging, and monitoring overall cluster health and performance. There's just one caveat: with 70+ fields and multiple records per query, interpreting the query log represents a steep learning curve. This initial version of query insights provides a blueprint for future work to simplify query debugging and optimization patterns. We'd love to hear your feedback as we continue to iterate on this feature, so please reach out—your input will be greatly appreciated.
Prometheus endpoint for metrics (private preview) {#prometheus-endpoint-for-metrics-private-preview}
Perhaps one of our most requested features: you can now export
Prometheus
metrics from ClickHouse Cloud to
Grafana
and
Datadog
for visualization. Prometheus provides an open-source solution to monitor ClickHouse and set up custom alerts. Access to Prometheus metrics for your ClickHouse Cloud service is available via the
ClickHouse Cloud API
. This feature is currently in Private Preview. Please reach out to the
support team
to enable this feature for your organization.
Other features {#other-features}
Configurable backups
to configure custom backup policies like frequency, retention, and schedule are now Generally Available.
June 13, 2024 {#june-13-2024}
Configurable offsets for Kafka ClickPipes Connector (Beta) {#configurable-offsets-for-kafka-clickpipes-connector-beta}
Until recently, whenever you set up a new
Kafka Connector for ClickPipes
, it always consumed data from the beginning of the Kafka topic. In this situation, it may not be flexible enough to fit specific use cases when you need to reprocess historical data, monitor new incoming data, or resume from a precise point.
ClickPipes for Kafka has added a new feature that enhances the flexibility and control over data consumption from Kafka topics. You can now configure the offset from which data is consumed. | {"source_file": "01_changelog.md"} | [
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0... |
c98e5675-d099-4f25-b5f5-e2123d677c75 | ClickPipes for Kafka has added a new feature that enhances the flexibility and control over data consumption from Kafka topics. You can now configure the offset from which data is consumed.
The following options are available:
- From the beginning: Start consuming data from the very beginning of the Kafka topic. This option is ideal for users who need to reprocess all historical data.
- From latest: Begin consuming data from the most recent offset. This is useful for users who are only interested in new messages.
- From a timestamp: Start consuming data from messages that were produced at or after a specific timestamp. This feature allows for more precise control, enabling users to resume processing from an exact point in time.
Enroll services to the Fast release channel {#enroll-services-to-the-fast-release-channel}
The Fast release channel allows your services to receive updates ahead of the release schedule. Previously, this feature required assistance from the support team to enable. Now, you can use the ClickHouse Cloud console to enable this feature for your services directly. Simply navigate to
Settings
, and click
Enroll in fast releases
. Your service will now receive updates as soon as they are available.
Terraform support for horizontal scaling {#terraform-support-for-horizontal-scaling}
ClickHouse Cloud supports
horizontal scaling
, or the ability to add additional replicas of the same size to your services. Horizontal scaling improves performance and parallelization to support concurrent queries. Previously, adding more replicas required either using the ClickHouse Cloud console or the API. You can now use Terraform to add or remove replicas from your service, allowing you to programmatically scale your ClickHouse services as needed.
Please see the
ClickHouse Terraform provider
for more information.
May 30, 2024 {#may-30-2024}
Share queries with your teammates {#share-queries-with-your-teammates}
When you write a SQL query, there's a good chance that other people on your team would also find that query useful. Previously, you'd have to send a query over Slack or email and there would be no way for a teammate to automatically receive updates for that query if you edit it.
We're happy to announce that you can now easily share queries via the ClickHouse Cloud console. From the query editor, you can share a query directly with your entire team or a specific team member. You can also specify whether they have read or write only access. Click on the
Share
button in the query editor to try out the new shared queries feature.
ClickHouse Cloud for Microsoft Azure is now in beta {#clickhouse-cloud-for-microsoft-azure-is-now-in-beta} | {"source_file": "01_changelog.md"} | [
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73fb5b83-f5b2-4b06-ab97-1360635de31d | ClickHouse Cloud for Microsoft Azure is now in beta {#clickhouse-cloud-for-microsoft-azure-is-now-in-beta}
We've finally launched the ability to create ClickHouse Cloud services on Microsoft Azure. We already have many customers using ClickHouse Cloud on Azure in production as part of our Private Preview program. Now, anyone can create their own service on Azure. All of your favorite ClickHouse features that are supported on AWS and GCP will also work on Azure.
We expect to have ClickHouse Cloud for Azure ready for General Availability in the next few weeks.
Read this blog post
to learn more, or create your new service using Azure via the ClickHouse Cloud console.
Note:
Development
services for Azure are not supported at this time.
Set up Private Link via the Cloud console {#set-up-private-link-via-the-cloud-console}
Our Private Link feature allows you to connect your ClickHouse Cloud services with internal services in your cloud provider account without having to direct traffic to the public internet, saving costs and enhancing security. Previously, this was difficult to set up and required using the ClickHouse Cloud API.
You can now configure private endpoints in just a few clicks directly from the ClickHouse Cloud console. Simply go to your service's
Settings
, go to the
Security
section and click
Set up private endpoint
.
May 17, 2024 {#may-17-2024}
Ingest data from Amazon Kinesis using ClickPipes (beta) {#ingest-data-from-amazon-kinesis-using-clickpipes-beta}
ClickPipes is an exclusive service provided by ClickHouse Cloud to ingest data without code. Amazon Kinesis is AWS's fully managed streaming service to ingest and store data streams for processing. We are thrilled to launch the ClickPipes beta for Amazon Kinesis, one of our most requested integrations. We're looking to add more integrations to ClickPipes, so please let us know which data source you'd like us to support. Read more about this feature
here
.
You can try the new Amazon Kinesis integration for ClickPipes in the cloud console:
Configurable backups (private preview) {#configurable-backups-private-preview}
Backups are important for every database (no matter how reliable), and we've taken backups very seriously since day 1 of ClickHouse Cloud. This week, we launched Configurable Backups, which allows for much more flexibility for your service's backups. You can now control start time, retention, and frequency. This feature is available for
Production
and
Dedicated
services and is not available for
Development
services. As this feature is in private preview, please contact support@clickhouse.com to enable this for your service. Read more about configurable backups
here
.
Create APIs from your SQL queries (Beta) {#create-apis-from-your-sql-queries-beta} | {"source_file": "01_changelog.md"} | [
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4e56d1e6-b9b9-4e24-9126-891d18eba65f | Create APIs from your SQL queries (Beta) {#create-apis-from-your-sql-queries-beta}
When you write a SQL query for ClickHouse, you still need to connect to ClickHouse via a driver to expose your query to your application. Now with our now
Query Endpoints
feature, you can execute SQL queries directly from an API without any configuration. You can specify the query endpoints to return JSON, CSV, or TSVs. Click the "Share" button in the cloud console to try this new feature with your queries. Read more about Query Endpoints
here
.
Official ClickHouse Certification is now available {#official-clickhouse-certification-is-now-available}
There are 12 free training modules in ClickHouse Develop training course. Prior to this week, there was no official way to prove your mastery in ClickHouse. We recently launched an official exam to become a
ClickHouse Certified Developer
. Completing this exam allows you to share with current and prospective employers your mastery in ClickHouse on topics including data ingestion, modeling, analysis, performance optimization, and more. You can take the exam
here
or read more about ClickHouse certification in this
blog post
.
April 25, 2024 {#april-25-2024}
Load data from S3 and GCS using ClickPipes {#load-data-from-s3-and-gcs-using-clickpipes}
You may have noticed in our newly released cloud console that there's a new section called "Data sources". The "Data sources" page is powered by ClickPipes, a native ClickHouse Cloud feature which lets you easily insert data from a variety of sources into ClickHouse Cloud.
Our most recent ClickPipes update features the ability to directly upload data directly from Amazon S3 and Google Cloud Storage. While you can still use our built-in table functions, ClickPipes is a fully-managed service via our UI that will let you ingest data from S3 and GCS in just a few clicks. This feature is still in Private Preview, but you can try it out today via the cloud console.
Use Fivetran to load data from 500+ sources into ClickHouse Cloud {#use-fivetran-to-load-data-from-500-sources-into-clickhouse-cloud}
ClickHouse can quickly query all of your large datasets, but of course, your data must first be inserted into ClickHouse. Thanks to Fivetran's comprehensive range of connectors, users can now quickly load data from over 500 sources. Whether you need to load data from Zendesk, Slack, or any of your favorite applications, the new ClickHouse destination for Fivetran now lets you use ClickHouse as the target database for your application data.
This is an open-source integration built over many months of hard work by our Integrations team. You can check out our
release blog post
here and the
GitHub repository
.
Other changes {#other-changes}
Console changes
- Output formats support in the SQL console
Integrations changes
- ClickPipes Kafka connector supports multi-broker setup
- PowerBI connector supports providing ODBC driver configuration options. | {"source_file": "01_changelog.md"} | [
-0.014298005029559135,
-0.07685597240924835,
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0.06213025748729706,
-0.06614571809768677,
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0.0396835096180439,
-0.002500944770872593,
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0.10284483432769775,
0.014... |
5566c9f6-b248-45cb-b5c7-0799440314ae | - Output formats support in the SQL console
Integrations changes
- ClickPipes Kafka connector supports multi-broker setup
- PowerBI connector supports providing ODBC driver configuration options.
April 18, 2024 {#april-18-2024}
AWS Tokyo region is now available for ClickHouse Cloud {#aws-tokyo-region-is-now-available-for-clickhouse-cloud}
This release introduces the new AWS Tokyo region (
ap-northeast-1
) for ClickHouse Cloud. Because we want ClickHouse to be the fastest database, we are continuously adding more regions for every cloud to reduce latency as much as possible. You can create your new service in Tokyo in the updated cloud console.
Other changes:
Console changes {#console-changes}
Avro format support for ClickPipes for Kafka is now Generally Available
Implement full support for importing resources (services and private endpoints) for the Terraform provider
Integrations changes {#integrations-changes}
NodeJS client major stable release: Advanced TypeScript support for query + ResultSet, URL configuration
Kafka Connector: Fixed a bug with ignoring exceptions when writing into DLQ, added support for Avro Enum type, published guides for using the connector on
MSK
and
Confluent Cloud
Grafana: Fixed support Nullable type support in UI, fixed support for dynamic OTEL tracing table name
DBT: Fixed model settings for custom materialization.
Java client: Fixed bug with incorrect error code parsing
Python client: Fixed parameters binding for numeric types, fixed bugs with number list in query binding, added SQLAlchemy Point support.
April 4, 2024 {#april-4-2024}
Introducing the new ClickHouse Cloud console {#introducing-the-new-clickhouse-cloud-console}
This release introduces a private preview for the new cloud console.
At ClickHouse, we are constantly thinking about how to improve the developer experience. We recognize that it is not enough to provide the fastest real-time data warehouse, it also needs to be easy to use and manage.
Thousands of ClickHouse Cloud users execute billions of queries on our SQL console every month, which is why we've decided to invest more in a world-class console to make it easier than ever to interact with your ClickHouse Cloud services. Our new cloud console experience combines our standalone SQL editor with our management console in one intuitive UI.
Select customers will receive a preview of our new cloud console experience – a unified and immersive way to explore and manage your data in ClickHouse. Please reach out to us at support@clickhouse.com if you'd like priority access.
March 28, 2024 {#march-28-2024}
This release introduces support for Microsoft Azure, Horizontal Scaling via API, and Release Channels in Private Preview.
General updates {#general-updates}
Introduced support for Microsoft Azure in Private Preview. To gain access, please reach out to account management or support, or join the
waitlist
. | {"source_file": "01_changelog.md"} | [
0.009788738563656807,
-0.08067423105239868,
-0.049745094031095505,
0.0010578552028164268,
-0.014769342727959156,
0.01625404693186283,
-0.07642236351966858,
-0.019356636330485344,
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0.07036259770393372,
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... |
8c457703-fe04-4e87-b5f5-7eed5032081b | General updates {#general-updates}
Introduced support for Microsoft Azure in Private Preview. To gain access, please reach out to account management or support, or join the
waitlist
.
Introduced Release Channels – the ability to specify the timing of upgrades based on environment type. In this release, we added the "fast" release channel, which enables you to upgrade your non-production environments ahead of production (please contact support to enable).
Administration changes {#administration-changes}
Added support for horizontal scaling configuration via API (private preview, please contact support to enable)
Improved autoscaling to scale up services encountering out of memory errors on startup
Added support for CMEK for AWS via the Terraform provider
Console changes {#console-changes-1}
Added support for Microsoft social login
Added parameterized query sharing capabilities in SQL console
Improved query editor performance significantly (from 5 secs to 1.5 sec latency in some EU regions)
Integrations changes {#integrations-changes-1}
ClickHouse OpenTelemetry exporter:
Added support
for ClickHouse replication table engine and
added integration tests
ClickHouse DBT adapter: Added support for
materialization macro for dictionaries
,
tests for TTL expression support
ClickHouse Kafka Connect Sink:
Added compatibility
with Kafka plugin discovery (community contribution)
ClickHouse Java Client: Introduced
a new package
for new client API and
added test coverage
for Cloud tests
ClickHouse NodeJS Client: Extended tests and documentation for new HTTP keep-alive behavior. Available since v0.3.0 release
ClickHouse Golang Client:
Fixed a bug
for Enum as a key in Map;
fixed a bug
when an errored connection is left in the connection pool (community contribution)
ClickHouse Python Client:
Added support
for query streaming via PyArrow (community contribution)
Security updates {#security-updates}
Updated ClickHouse Cloud to prevent
"Role-based Access Control is bypassed when query caching is enabled"
(CVE-2024-22412)
March 14, 2024 {#march-14-2024}
This release makes available in early access the new Cloud console experience, ClickPipes for bulk loading from S3 and GCS, and support for Avro format in ClickPipes for Kafka. It also upgrades the ClickHouse database version to 24.1, bringing support for new functions as well as performance and resource usage optimizations.
Console changes {#console-changes-2}
New Cloud console experience is available in early access (please contact support if you're interested in participating).
ClickPipes for bulk loading from S3 and GCS are available in early access (please contact support if you're interested in participating).
Support for Avro format in ClickPipes for Kafka is available in early access (please contact support if you're interested in participating).
ClickHouse version upgrade {#clickhouse-version-upgrade} | {"source_file": "01_changelog.md"} | [
-0.022618401795625687,
-0.027529126033186913,
0.013418336398899555,
0.017694978043437004,
0.04459105432033539,
0.028260603547096252,
-0.04501396790146828,
-0.023711854591965675,
-0.0556330606341362,
0.14782342314720154,
-0.016511067748069763,
-0.008950388990342617,
-0.01938013918697834,
-0... |
80aff339-498d-4c69-bb7c-6118bbbfab6c | ClickHouse version upgrade {#clickhouse-version-upgrade}
Optimizations for FINAL, vectorization improvements, faster aggregations - see
23.12 release blog
for details.
New functions for processing punycode, string similarity, detecting outliers, as well as memory optimizations for merges and Keeper - see
24.1 release blog
and
presentation
for details.
This ClickHouse cloud version is based on 24.1, you can see dozens of new features, performance improvements, and bug fixes. See core database
changelogs
for details.
Integrations changes {#integrations-changes-2}
Grafana: Fixed dashboard migration for v4, ad-hoc filtering logic
Tableau Connector: Fixed DATENAME function and rounding for "real" arguments
Kafka Connector: Fixed NPE in connection initialization, added ability to specify JDBC driver options
Golang client: Reduced the memory footprint for handling responses, fixed Date32 extreme values, fixed error reporting when compression is enabled
Python client: Improved timezone support in datetime parameters, improved performance for Pandas DataFrame
February 29, 2024 {#february-29-2024}
This release improves SQL console application load time, adds support for SCRAM-SHA-256 authentication in ClickPipes, and extends nested structure support to Kafka Connect.
Console changes {#console-changes-3}
Optimized SQL console application initial load time
Fixed SQL console race condition resulting in 'authentication failed' error
Fixed behavior on the monitoring page where most recent memory allocation value was sometimes incorrect
Fixed behavior where SQL console sometimes issue duplicate KILL QUERY commands
Added support in ClickPipes for SCRAM-SHA-256 authentication method for Kafka-based data sources
Integrations changes {#integrations-changes-3}
Kafka Connector: Extended support for complex nested structures (Array, Map); added support for FixedString type; added support for ingestion into multiple databases
Metabase: Fixed incompatibility with ClickHouse lower than version 23.8
DBT: Added the ability to pass settings to model creation
Node.js client: Added support for long-running queries (>1hr) and handling of empty values gracefully
February 15, 2024 {#february-15-2024}
This release upgrades the core database version, adds ability to set up private links via Terraform, and adds support for exactly once semantics for asynchronous inserts through Kafka Connect.
ClickHouse version upgrade {#clickhouse-version-upgrade-1}
S3Queue table engine for continuous, scheduled data loading from S3 is production-ready -
see 23.11 release blog
for details.
Significant performance improvements for FINAL and vectorization improvements for SIMD instructions resulting in faster queries -
see 23.12 release blog
for details. | {"source_file": "01_changelog.md"} | [
-0.060360126197338104,
-0.04605992138385773,
-0.0480034165084362,
-0.0280064158141613,
-0.020557815209031105,
-0.04647371545433998,
-0.08624720573425293,
-0.005617070011794567,
-0.07721097022294998,
0.0547666996717453,
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0.01847762241959572,
-0.042643602937459946,
-0.04... |
2bb9556e-35db-43b4-ae46-c3de621a6276 | Significant performance improvements for FINAL and vectorization improvements for SIMD instructions resulting in faster queries -
see 23.12 release blog
for details.
This ClickHouse cloud version is based on 23.12, you can see dozens of new features, performance improvements, and bug fixes. See
core database changelogs
for details.
Console changes {#console-changes-4}
Added ability to set up AWS Private Link and GCP Private Service Connect through Terraform provider
Improved resiliency for remote file data imports
Added import status details flyout to all data imports
Added key/secret key credential support to s3 data imports
Integrations changes {#integrations-changes-4}
Kafka Connect
Support async_insert for exactly once (disabled by default)
Golang client
Fixed DateTime binding
Improved batch insert performance
Java client
Fixed request compression problem
Settings changes {#settings-changes}
use_mysql_types_in_show_columns
is no longer required. It will be automatically enabled when you connect through the MySQL interface.
async_insert_max_data_size
now has the default value of
10 MiB
February 2, 2024 {#february-2-2024}
This release brings availability of ClickPipes for Azure Event Hub, dramatically improves workflow for logs and traces navigation using v4 ClickHouse Grafana connector, and debuts support for Flyway and Atlas database schema management tools.
Console changes {#console-changes-5}
Added ClickPipes support for Azure Event Hub
New services are launched with default idling time of 15 mins
Integrations changes {#integrations-changes-5}
ClickHouse data source for Grafana
v4 release
Completely rebuilt query builder to have specialized editors for Table, Logs, Time Series, and Traces
Completely rebuilt SQL generator to support more complicated and dynamic queries
Added first-class support for OpenTelemetry in Log and Trace views
Extended Configuration to allow to specify default tables and columns for Logs and Traces
Added ability to specify custom HTTP headers
And many more improvements - check the full
changelog
Database schema management tools
Flyway added ClickHouse support
Ariga Atlas added ClickHouse support
Kafka Connector Sink
Optimized ingestion into a table with default values
Added support for string-based dates in DateTime64
Metabase
Added support for a connection to multiple databases
January 18, 2024 {#january-18-2024}
This release brings a new region in AWS (London / eu-west-2), adds ClickPipes support for Redpanda, Upstash, and Warpstream, and improves reliability of the
is_deleted
core database capability.
General changes {#general-changes}
New AWS Region: London (eu-west-2)
Console changes {#console-changes-6}
Added ClickPipes support for Redpanda, Upstash, and Warpstream
Made the ClickPipes authentication mechanism configurable in the UI
Integrations changes {#integrations-changes-6} | {"source_file": "01_changelog.md"} | [
-0.057148855179548264,
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0.03064250759780407,
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0.02476389892399311,
-0.... |
6c35b45c-1f20-4970-a20c-123d76f1ca27 | Added ClickPipes support for Redpanda, Upstash, and Warpstream
Made the ClickPipes authentication mechanism configurable in the UI
Integrations changes {#integrations-changes-6}
Java client:
Breaking changes: Removed the ability to specify random URL handles in the call. This functionality has been removed from ClickHouse
Deprecations: Java CLI client and GRPC packages
Added support for RowBinaryWithDefaults format to reduce the batch size and workload on ClickHouse instance (request by Exabeam)
Made Date32 and DateTime64 range boundaries compatible with ClickHouse, compatibility with Spark Array string type, node selection mechanism
Kafka Connector: Added a JMX monitoring dashboard for Grafana
PowerBI: Made ODBC driver settings configurable in the UI
JavaScript client: Exposed query summary information, allow to provide a subset of specific columns for insertion, make keep_alive configurable for web client
Python client: Added Nothing type support for SQLAlchemy
Reliability changes {#reliability-changes}
User-facing backward incompatible change: Previously, two features (
is_deleted
and
OPTIMIZE CLEANUP
) under certain conditions could lead to corruption of the data in ClickHouse. To protect the integrity of the data of our users, while keeping the core of the functionality, we adjusted how this feature works. Specifically, the MergeTree setting
clean_deleted_rows
is now deprecated and has no effect anymore. The
CLEANUP
keyword is not allowed by default (to use it you will need to enable
allow_experimental_replacing_merge_with_cleanup
). If you decide to use
CLEANUP
, you need to make sure that it is always used together with
FINAL
, and you must guarantee that no rows with older versions will be inserted after you run
OPTIMIZE FINAL CLEANUP
.
December 18, 2023 {#december-18-2023}
This release brings a new region in GCP (us-east1), ability to self-service secure endpoint connections, support for additional integrations including DBT 1.7, and numerous bug fixes and security enhancements.
General changes {#general-changes-1}
ClickHouse Cloud is now available in GCP us-east1 (South Carolina) region
Enabled ability to set up AWS Private Link and GCP Private Service Connect via OpenAPI
Console changes {#console-changes-7}
Enabled seamless login to SQL console for users with the Developer role
Streamlined workflow for setting idling controls during onboarding
Integrations changes {#integrations-changes-7}
DBT connector: Added support for DBT up to v1.7
Metabase: Added support for Metabase v0.48
PowerBI Connector: Added ability to run on PowerBI Cloud
Make permissions for ClickPipes internal user configurable
Kafka Connect
Improved deduplication logic and ingestion of Nullable types.
Add support text-based formats (CSV, TSV)
Apache Beam: add support for Boolean and LowCardinality types
Nodejs client: add support for Parquet format | {"source_file": "01_changelog.md"} | [
-0.12100069224834442,
-0.052269116044044495,
-0.07795953005552292,
-0.01755273900926113,
-0.04346872493624687,
-0.07007256895303726,
-0.022399570792913437,
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0.019247492775321007,
-0.029546068981289864,
... |
ffbe473e-bcdb-4cee-acd8-bc90de9ad070 | Add support text-based formats (CSV, TSV)
Apache Beam: add support for Boolean and LowCardinality types
Nodejs client: add support for Parquet format
Security announcements {#security-announcements}
Patched 3 security vulnerabilities - see
security changelog
for details:
CVE 2023-47118 (CVSS 7.0) - a heap buffer overflow vulnerability affecting the native interface running by default on port 9000/tcp
CVE-2023-48704 (CVSS 7.0) - a heap buffer overflow vulnerability affecting the native interface running by default on port 9000/tcp
CVE 2023-48298 (CVSS 5.9) - an integer underflow vulnerability in the FPC compressions codec
November 22, 2023 {#november-22-2023}
This release upgrades the core database version, improves login and authentication flow, and adds proxy support to Kafka Connect Sink.
ClickHouse version upgrade {#clickhouse-version-upgrade-2}
Dramatically improved performance for reading Parquet files. See
23.8 release blog
for details.
Added type inference support for JSON. See
23.9 release blog
for details.
Introduced powerful analyst-facing functions like
ArrayFold
. See
23.10 release blog
for details.
User-facing backward-incompatible change
: Disabled setting
input_format_json_try_infer_numbers_from_strings
by default to avoid inferring numbers from strings in JSON format. Doing so can create possible parsing errors when sample data contains strings similar to numbers.
Dozens of new features, performance improvements, and bug fixes. See
core database changelogs
for details.
Console changes {#console-changes-8}
Improved login and authentication flow.
Improved AI-based query suggestions to better support large schemas.
Integrations changes {#integrations-changes-8}
Kafka Connect Sink: Added proxy support,
topic-tablename
mapping, and configurability for Keeper
exactly-once
delivery properties.
Node.js client: Added support for Parquet format.
Metabase: Added
datetimeDiff
function support.
Python client: Added support for special characters in column names. Fixed timezone parameter binding.
November 2, 2023 {#november-2-2023}
This release adds more regional support for development services in Asia, introduces key rotation functionality to customer-managed encryption keys, improved granularity of tax settings in the billing console and a number of bug fixes across supported language clients.
General updates {#general-updates-1}
Development services are now available in AWS for
ap-south-1
(Mumbai) and
ap-southeast-1
(Singapore)
Added support for key rotation in customer-managed encryption keys (CMEK)
Console changes {#console-changes-9}
Added ability to configure granular tax settings when adding a credit card
Integrations changes {#integrations-changes-9}
MySQL
Improved Tableau Online and QuickSight support via MySQL
Kafka Connector
Introduced a new StringConverter to support text-based formats (CSV, TSV) | {"source_file": "01_changelog.md"} | [
-0.10456342250108719,
0.016417786478996277,
-0.035659704357385635,
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0.003965435083955526,
-0.026695188134908676,
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0.05237073823809624,
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0.010337005369365215,
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0.01293404120951891,
-0.07830911129713058,
0.... |
d1f12b1f-a5ce-49c0-8cb9-fbb593bc5635 | MySQL
Improved Tableau Online and QuickSight support via MySQL
Kafka Connector
Introduced a new StringConverter to support text-based formats (CSV, TSV)
Added support for Bytes and Decimal data types
Adjusted Retryable Exceptions to now always be retried (even when errors.tolerance=all)
Node.js client
Fixed an issue with streamed large datasets providing corrupted results
Python client
Fixed timeouts on large inserts
Fixed NumPy/Pandas Date32 issue
- Golang client
Fixed insertion of an empty map into JSON column, compression buffer cleanup, query escaping, panic on zero/nil for IPv4 and IPv6
Added watchdog on canceled inserts
DBT
Improved distributed table support with tests
October 19, 2023 {#october-19-2023}
This release brings usability and performance improvements in the SQL console, better IP data type handling in the Metabase connector, and new functionality in the Java and Node.js clients.
Console changes {#console-changes-10}
Improved usability of the SQL console (e.g. preserve column width between query executions)
Improved performance of the SQL console
Integrations changes {#integrations-changes-10}
Java client:
Switched the default network library to improve performance and reuse open connections
Added proxy support
Added support for secure connections with using Trust Store
Node.js client: Fixed keep-alive behavior for insert queries
Metabase: Fixed IPv4/IPv6 column serialization
September 28, 2023 {#september-28-2023}
This release brings general availability of ClickPipes for Kafka, Confluent Cloud, and Amazon MSK and the Kafka Connect ClickHouse Sink, self-service workflow to secure access to Amazon S3 via IAM roles, and AI-assisted query suggestions ( private preview).
Console changes {#console-changes-11}
Added a self-service workflow to secure
access to Amazon S3 via IAM roles
Introduced AI-assisted query suggestions in private preview (please
contact ClickHouse Cloud support
to try it out.)
Integrations changes {#integrations-changes-11}
Announced general availability of ClickPipes - a turnkey data ingestion service - for Kafka, Confluent Cloud, and Amazon MSK (see the
release blog
)
Reached general availability of Kafka Connect ClickHouse Sink
Extended support for customized ClickHouse settings using
clickhouse.settings
property
Improved deduplication behavior to account for dynamic fields
Added support for
tableRefreshInterval
to re-fetch table changes from ClickHouse
Fixed an SSL connection issue and type mappings between
PowerBI
and ClickHouse data types
September 7, 2023 {#september-7-2023}
This release brings the beta release of the PowerBI Desktop official connector, improved credit card payment handling for India, and multiple improvements across supported language clients.
Console changes {#console-changes-12}
Added remaining credits and payment retries to support charges from India | {"source_file": "01_changelog.md"} | [
-0.035383161157369614,
-0.012536483816802502,
-0.02213190495967865,
0.024969106540083885,
0.00047228753101080656,
-0.028558935970067978,
-0.06102791428565979,
0.052415456622838974,
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0.03837720304727554,
0.04093022271990776,
... |
248b56c3-ea6e-48e9-8769-0c879960d726 | Console changes {#console-changes-12}
Added remaining credits and payment retries to support charges from India
Integrations changes {#integrations-changes-12}
Kafka Connector: added support for configuring ClickHouse settings, added error.tolerance configuration option
PowerBI Desktop: released the beta version of the official connector
Grafana: added support for Point geo type, fixed Panels in Data Analyst dashboard, fixed timeInterval macro
Python client: Compatible with Pandas 2.1.0, dropped Python 3.7 support, added support for nullable JSON type
Node.js client: added default_format setting support
Golang client: fixed bool type handling, removed string limits
Aug 24, 2023 {#aug-24-2023}
This release adds support for the MySQL interface to the ClickHouse database, introduces a new official PowerBI connector, adds a new "Running Queries" view in the cloud console, and updates the ClickHouse version to 23.7.
General updates {#general-updates-2}
Added support for the
MySQL wire protocol
, which (among other use cases) enables compatibility with many existing BI tools. Please reach out to support to enable this feature for your organization.
Introduced a new official PowerBI connector
Console changes {#console-changes-13}
Added support for "Running Queries" view in SQL Console
ClickHouse 23.7 version upgrade {#clickhouse-237-version-upgrade}
Added support for Azure Table function, promoted geo datatypes to production-ready, and improved join performance - see 23.5 release
blog
for details
Extended MongoDB integration support to version 6.0 - see 23.6 release
blog
for details
Improved performance of writing to Parquet format by 6x, added support for PRQL query language, and improved SQL compatibility - see 23.7 release
deck
for details
Dozens of new features, performance improvements, and bug fixes - see detailed
changelogs
for 23.5, 23.6, 23.7
Integrations changes {#integrations-changes-13}
Kafka Connector: Added support for Avro Date and Time types
JavaScript client: Released a stable version for web-based environment
Grafana: Improved filter logic, database name handling, and added support for TimeInteval with sub-second precision
Golang Client: Fixed several batch and async data loading issues
Metabase: Support v0.47, added connection impersonation, fixed data types mappings
July 27, 2023 {#july-27-2023}
This release brings the private preview of ClickPipes for Kafka, a new data loading experience, and the ability to load a file from a URL using the cloud console.
Integrations changes {#integrations-changes-14}
Introduced the private preview of
ClickPipes
for Kafka, a cloud-native integration engine that makes ingesting massive volumes of data from Kafka and Confluent Cloud as simple as clicking a few buttons. Please sign up for the waitlist
here
. | {"source_file": "01_changelog.md"} | [
-0.0831175297498703,
-0.025535425171256065,
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0.0023161773569881916,
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0.00009221588697982952,
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0.002692602341994643,
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0.04776234179735184,
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... |
184cd88e-d4d8-47fb-89af-f577fea5bc44 | JavaScript client: released support for web-based environment (browser, Cloudflare workers). The code is refactored to allow community creating connectors for custom environments.
Kafka Connector: Added support for inline schema with Timestamp and Time Kafka types
Python client: Fixed insert compression and LowCardinality reading issues
Console changes {#console-changes-14}
Added a new data loading experience with more table creation configuration options
Introduced ability to load a file from a URL using the cloud console
Improved invitation flow with additional options to join a different organization and see all your outstanding invitations
July 14, 2023 {#july-14-2023}
This release brings the ability to spin up Dedicated Services, a new AWS region in Australia, and the ability to bring your own key for encrypting data on disk.
General updates {#general-updates-3}
New AWS Australia region: Sydney (ap-southeast-2)
Dedicated tier services for demanding latency-sensitive workloads (please contact
support
to set it up)
Bring your own key (BYOK) for encrypting data on disk (please contact
support
to set it up)
Console changes {#console-changes-15}
Improvements to observability metrics dashboard for asynchronous inserts
Improved chatbot behavior for integration with support
Integrations changes {#integrations-changes-15}
NodeJS client: fixed a bug with a connection failure due to socket timeout
Python client: added QuerySummary to insert queries, support special characters in the database name
Metabase: updated JDBC driver version, added DateTime64 support, performance improvements.
Core database changes {#core-database-changes}
Query cache
can be enabled in ClickHouse Cloud. When it is enabled, successful queries are cached for a minute by default and subsequent queries will use the cached result.
June 20, 2023 {#june-20-2023}
This release makes ClickHouse Cloud on GCP generally available, brings a Terraform provider for the Cloud API, and updates the ClickHouse version to 23.4.
General updates {#general-updates-4}
ClickHouse Cloud on GCP is now GA, bringing GCP Marketplace integration, support for Private Service Connect, and automatic backups (see
blog
and
press release
for details)
Terraform provider
for Cloud API is now available
Console changes {#console-changes-16}
Added a new consolidated settings page for services
Adjusted metering accuracy for storage and compute
Integrations changes {#integrations-changes-16}
Python client: improved insert performance, refactored internal dependencies to support multiprocessing
Kafka Connector: It can be uploaded and installed on Confluent Cloud, added retry for interim connection problems, reset the incorrect connector state automatically
ClickHouse 23.4 version upgrade {#clickhouse-234-version-upgrade}
Added JOIN support for parallel replicas (please contact
support
to set it up) | {"source_file": "01_changelog.md"} | [
-0.09160677343606949,
-0.02373713254928589,
-0.03906458616256714,
-0.004022574983537197,
0.0022228930611163378,
-0.006248967722058296,
-0.08363417536020279,
-0.014428386464715004,
0.062010426074266434,
0.12433351576328278,
-0.02719404175877571,
0.020277325063943863,
0.005191815085709095,
0... |
e6b1b6da-c97d-4dd1-9236-64b82ce7b494 | ClickHouse 23.4 version upgrade {#clickhouse-234-version-upgrade}
Added JOIN support for parallel replicas (please contact
support
to set it up)
Improved performance of lightweight deletes
Improved caching while processing large inserts
Administration changes {#administration-changes-1}
Expanded local dictionary creation for non "default" users
May 30, 2023 {#may-30-2023}
This release brings the public release of the ClickHouse Cloud Programmatic API for Control Plane operations (see
blog
for details), S3 access using IAM roles, and additional scaling options.
General changes {#general-changes-2}
API Support for ClickHouse Cloud. With the new Cloud API, you can seamlessly integrate managing services in your existing CI/CD pipeline and manage your services programmatically
S3 access using IAM roles. You can now leverage IAM roles to securely access your private Amazon Simple Storage Service (S3) buckets (please contact support to set it up)
Scaling changes {#scaling-changes}
Horizontal scaling
. Workloads that require more parallelization can now be configured with up to 10 replicas (please contact support to set it up)
CPU based autoscaling
. CPU-bound workloads can now benefit from additional triggers for autoscaling policies
Console changes {#console-changes-17}
Migrate Dev service to Production service (please contact support to enable)
Added scaling configuration controls during instance creation flows
Fix connection string when default password is not present in memory
Integrations changes {#integrations-changes-17}
Golang client: fixed a problem leading to unbalanced connections in native protocol, added support for the custom settings in the native protocol
Nodejs client: dropped support for nodejs v14, added support for v20
Kafka Connector: added support for LowCardinality type
Metabase: fixed grouping by a time range, fixed support for integers in built-in Metabase questions
Performance and reliability {#performance-and-reliability}
Improved efficiency and performance of write heavy workloads
Deployed incremental backup strategy to increase speed and efficiency of backups
May 11, 2023 {#may-11-2023}
This release brings the public beta of ClickHouse Cloud on GCP
(see
blog
for details), extends administrators' rights to grant terminate query permissions,
and adds more visibility into the status of MFA users in the Cloud console.
:::note Update
ClickHouse Cloud on GCP is now GA, see the entry for June twenty above.
:::
ClickHouse Cloud on GCP is now available in public beta {#clickhouse-cloud-on-gcp-is-now-available-in-public-beta-now-ga-see-june-20th-entry-above}
:::note
ClickHouse Cloud on GCP is now GA, see the
June 20th
entry above.
:::
Launches a fully-managed separated storage and compute ClickHouse offering, running on top of Google Compute and Google Cloud Storage | {"source_file": "01_changelog.md"} | [
-0.036064617335796356,
-0.04683336615562439,
-0.03617872670292854,
-0.04534865543246269,
-0.0191411841660738,
0.002414664486423135,
-0.07114625722169876,
-0.046208277344703674,
-0.008539702743291855,
0.09075476229190826,
0.026579052209854126,
-0.0034557811450213194,
0.06659567356109619,
-0... |
6a3c91b5-836b-436d-8501-dea0e0ba05e5 | Launches a fully-managed separated storage and compute ClickHouse offering, running on top of Google Compute and Google Cloud Storage
Available in Iowa (us-central1), Netherlands (europe-west4), and Singapore (asia-southeast1) regions
Supports both Development and Production services in all three initial regions
Provides strong security by default: End-to-end encryption in transit, data-at-rest encryption, IP Allow Lists
Integrations changes {#integrations-changes-18}
Golang client: Added proxy environment variables support
Grafana: Added the ability to specify ClickHouse custom settings and proxy environment variables in Grafana datasource setup
Kafka Connector: Improved handling of empty records
Console changes {#console-changes-18}
Added an indicator for multifactor authentication (MFA) use in the user list
Performance and reliability {#performance-and-reliability-1}
Added more granular control over terminate query permission for administrators
May 4, 2023 {#may-4-2023}
This release brings a new heatmap chart type, improves billing usage page, and improves service startup time.
Console changes {#console-changes-19}
Added heatmap chart type to SQL console
Improved billing usage page to show credits consumed within each billing dimension
Integrations changes {#integrations-changes-19}
Kafka connector: Added retry mechanism for transient connection errors
Python client: Added max_connection_age setting to ensure that HTTP connections are not reused forever. This can help with certain load-balancing issues
Node.js client: Added support for Node.js v20
Java client: Improved client certificate authentication support, and added support for nested Tuple/Map/Nested types
Performance and reliability {#performance-and-reliability-2}
Improved service startup time in presence of a large number of parts
Optimized long-running query cancellation logic in SQL console
Bug fixes {#bug-fixes}
Fixed a bug causing 'Cell Towers' sample dataset import to fail
April 20, 2023 {#april-20-2023}
This release updates the ClickHouse version to 23.3, significantly improves the speed of cold reads, and brings real-time chat with support.
Console changes {#console-changes-20}
Added an option for real-time chat with support
Integrations changes {#integrations-changes-20}
Kafka connector: Added support for Nullable types
Golang client: Added support for external tables, support boolean and pointer type parameter bindings
Configuration changes {#configuration-changes}
Adds ability to drop large tables–by overriding
max_table_size_to_drop
and
max_partition_size_to_drop
settings
Performance and reliability {#performance-and-reliability-3}
Improve speed of cold reads by the means of S3 prefetching via
allow_prefetched_read_pool_for_remote_filesystem
setting
ClickHouse 23.3 version upgrade {#clickhouse-233-version-upgrade} | {"source_file": "01_changelog.md"} | [
-0.07554207742214203,
-0.003122713416814804,
-0.04301784932613373,
-0.03544248268008232,
-0.08674570173025131,
0.023970291018486023,
-0.05977891758084297,
-0.01444255281239748,
-0.03448692336678505,
0.08225523680448532,
-0.018378522247076035,
-0.043235164135694504,
-0.0005376034532673657,
... |
2105ea8f-af7d-47c2-9ea9-2af41f311a23 | Improve speed of cold reads by the means of S3 prefetching via
allow_prefetched_read_pool_for_remote_filesystem
setting
ClickHouse 23.3 version upgrade {#clickhouse-233-version-upgrade}
Lightweight deletes are production-ready–see 23.3 release
blog
for details
Added support for multi-stage PREWHERE-see 23.2 release
blog
for details
Dozens of new features, performance improvements, and bug fixes–see detailed
changelogs
for 23.3 and 23.2
April 6, 2023 {#april-6-2023}
This release brings an API for retrieving cloud endpoints, an advanced scaling control for minimum idle timeout, and support for external data in Python client query methods.
API changes {#api-changes}
Added ability to programmatically query ClickHouse Cloud endpoints via
Cloud Endpoints API
Console changes {#console-changes-21}
Added 'minimum idle timeout' setting to advanced scaling settings
Added best-effort datetime detection to schema inference in data loading modal
Integrations changes {#integrations-changes-21}
Metabase
: Added support for multiple schemas
Go client
: Fixed idle connection liveness check for TLS connections
Python client
Added support for external data in query methods
Added timezone support for query results
Added support for
no_proxy
/
NO_PROXY
environment variable
Fixed server-side parameter binding of the NULL value for Nullable types
Bug fixes {#bug-fixes-1}
Fixed behavior where running
INSERT INTO ... SELECT ...
from the SQL console incorrectly applied the same row limit as select queries
March 23, 2023 {#march-23-2023}
This release brings database password complexity rules, significant speedup in restoring large backups, and support for displaying traces in Grafana Trace View.
Security and reliability {#security-and-reliability}
Core database endpoints now enforce password complexity rules
Improved time to restore large backups
Console changes {#console-changes-22}
Streamlined onboarding workflow, introducing new defaults and more compact views
Reduced sign-up and sign-in latencies
Integrations changes {#integrations-changes-22}
Grafana:
Added support for displaying trace data stored in ClickHouse in Trace View
Improved time range filters and added support for special characters in table names
Superset: Added native ClickHouse support
Kafka Connect Sink: Added automatic date conversion and Null column handling
Metabase: Implemented compatibility with v0.46
Python client: Fixed inserts in temporary tables and added support for Pandas Null
Golang client: Normalized Date types with timezone
Java client
Added to SQL parser support for compression, infile, and outfile keywords
Added credentials overload
Fixed batch support with
ON CLUSTER
Node.js client
Added support for JSONStrings, JSONCompact, JSONCompactStrings, JSONColumnsWithMetadata formats
query_id
can now be provided for all main client methods | {"source_file": "01_changelog.md"} | [
-0.05612074211239815,
-0.03324286639690399,
-0.020090922713279724,
0.0526791587471962,
0.03423051908612251,
-0.02992909774184227,
-0.06637037545442581,
-0.017462603747844696,
0.016453104093670845,
0.05567197501659393,
-0.02723114565014839,
0.05807105079293251,
-0.0009843203006312251,
-0.04... |
71a11b1a-c8b3-4907-a098-1ac7cae41498 | Node.js client
Added support for JSONStrings, JSONCompact, JSONCompactStrings, JSONColumnsWithMetadata formats
query_id
can now be provided for all main client methods
Bug fixes {#bug-fixes-2}
Fixed a bug resulting in slow initial provisioning and startup times for new services
Fixed a bug that resulted in slower query performance due to cache misconfiguration
March 9, 2023 {#march-9-2023}
This release improves observability dashboards, optimizes time to create large backups, and adds the configuration necessary to drop large tables and partitions.
Console changes {#console-changes-23}
Added advanced observability dashboards (preview)
Introduced a memory allocation chart to the observability dashboards
Improved spacing and newline handling in SQL Console spreadsheet view
Reliability and performance {#reliability-and-performance}
Optimized backup schedule to run backups only if data was modified
Improved time to complete large backups
Configuration changes {#configuration-changes-1}
Added the ability to increase the limit to drop tables and partitions by overriding the settings
max_table_size_to_drop
and
max_partition_size_to_drop
on the query or connection level
Added source IP to query log, to enable quota and access control enforcement based on source IP
Integrations {#integrations}
Python client
: Improved Pandas support and fixed timezone-related issues
Metabase
: Metabase 0.46.x compatibility and support for SimpleAggregateFunction
Kafka-Connect
: Implicit date conversion and better handling for null columns
Java Client
: Nested conversion to Java maps
February 23, 2023 {#february-23-2023}
This release enables a subset of the features in the ClickHouse 23.1 core release, brings interoperability with Amazon Managed Streaming for Apache Kafka (MSK), and exposes advanced scaling and idling adjustments in the activity log.
ClickHouse 23.1 version upgrade {#clickhouse-231-version-upgrade}
Adds support for a subset of features in ClickHouse 23.1, for example:
- ARRAY JOIN with Map type
- SQL standard hex and binary literals
- New functions, including
age()
,
quantileInterpolatedWeighted()
,
quantilesInterpolatedWeighted()
- Ability to use structure from insertion table in
generateRandom
without arguments
- Improved database creation and rename logic that allows the reuse of previous names
- See the 23.1 release
webinar slides
and
23.1 release changelog
for more details
Integrations changes {#integrations-changes-23}
Kafka-Connect
: Added support for Amazon MSK
Metabase
: First stable release 1.0.0
Made the connector is available on
Metabase Cloud
Added a feature to explore all available databases
Fixed synchronization of database with AggregationFunction type
DBT-clickhouse
: Added support for the latest DBT version v1.4.1 | {"source_file": "01_changelog.md"} | [
-0.05892603099346161,
0.008318137377500534,
-0.024207720533013344,
0.03691805154085159,
0.014665957540273666,
-0.017691370099782944,
-0.08881516754627228,
0.08356974273920059,
-0.05750526487827301,
0.027369970455765724,
-0.04638272896409035,
0.06728378683328629,
0.02002703957259655,
0.0066... |
45514c44-4ef7-4ef2-b3e4-264393a80571 | Added a feature to explore all available databases
Fixed synchronization of database with AggregationFunction type
DBT-clickhouse
: Added support for the latest DBT version v1.4.1
Python client
: Improved proxy and ssh tunneling support; added a number of fixes and performance optimizations for Pandas DataFrames
Nodejs client
: Released ability to attach
query_id
to query result, which can be used to retrieve query metrics from the
system.query_log
Golang client
: Optimized network connection with ClickHouse Cloud
Console changes {#console-changes-24}
Added advanced scaling and idling settings adjustments to the activity log
Added user agent and IP information to reset password emails
Improved signup flow mechanics for Google OAuth
Reliability and performance {#reliability-and-performance-1}
Speed up the resume time from idle for large services
Improved reading latency for services with a large number of tables and partitions
Bug fixes {#bug-fixes-3}
Fixed behavior where resetting service password did not adhere to the password policy
Made organization invite email validation case-insensitive
February 2, 2023 {#february-2-2023}
This release brings an officially supported Metabase integration, a major Java client / JDBC driver release, and support for views and materialized views in the SQL console.
Integrations changes {#integrations-changes-24}
Metabase
plugin: Became an official solution maintained by ClickHouse
dbt
plugin: Added support for
multiple threads
Grafana
plugin: Better handling of connection errors
Python
client:
Streaming support
for insert operation
Go
client:
Bug fixes
: close canceled connections, better handling of connection errors
JS
client:
Breaking changes in exec/insert
; exposed query_id in the return types
Java
client / JDBC driver major release
Breaking changes
: deprecated methods, classes and packages were removed
Added R2DBC driver and file insert support
Console changes {#console-changes-25}
Added support for views and materialized views in SQL console
Performance and reliability {#performance-and-reliability-4}
Faster password reset for stopped/idling instances
Improved the scale-down behavior via more accurate activity tracking
Fixed a bug where SQL console CSV export was truncated
Fixed a bug resulting in intermittent sample data upload failures
January 12, 2023 {#january-12-2023}
This release updates the ClickHouse version to 22.12, enables dictionaries for many new sources, and improves query performance.
General changes {#general-changes-3}
Enabled dictionaries for additional sources, including external ClickHouse, Cassandra, MongoDB, MySQL, PostgreSQL, and Redis
ClickHouse 22.12 version upgrade {#clickhouse-2212-version-upgrade}
Extended JOIN support to include Grace Hash Join
Added Binary JSON (BSON) support for reading files
Added support for GROUP BY ALL standard SQL syntax | {"source_file": "01_changelog.md"} | [
-0.07610651105642319,
-0.04773898422718048,
0.03910541534423828,
-0.01537586934864521,
-0.002337716519832611,
-0.029577314853668213,
-0.010613992810249329,
0.03374585136771202,
-0.07785212248563766,
0.0032029920257627964,
-0.02599051408469677,
0.0823701024055481,
0.008447526022791862,
-0.0... |
e529285a-7ed6-402d-82d8-9abbfe5cd3fb | Extended JOIN support to include Grace Hash Join
Added Binary JSON (BSON) support for reading files
Added support for GROUP BY ALL standard SQL syntax
New mathematical functions for decimal operations with fixed precision
See the
22.12 release blog
and
detailed 22.12 changelog
for the complete list of changes
Console changes {#console-changes-26}
Improved auto-complete capabilities in SQL Console
Default region now takes into account continent locality
Improved Billing Usage page to display both billing and website units
Integrations changes {#integrations-changes-25}
DBT release
v1.3.2
Added experimental support for the delete+insert incremental strategy
New s3source macro
Python client
v0.4.8
File insert support
Server-side query
parameters binding
Go client
v2.5.0
Reduced memory usage for compression
Server-side query
parameters binding
Reliability and performance {#reliability-and-performance-2}
Improved read performance for queries that fetch a large number of small files on object store
Set the
compatibility
setting to the version with which the service is initially launched, for newly launched services
Bug fixes {#bug-fixes-4}
Using the Advanced Scaling slider to reserve resources now takes effect right away.
December 20, 2022 {#december-20-2022}
This release introduces seamless logins for administrators to SQL console, improved read performance for cold reads, and an improved Metabase connector for ClickHouse Cloud.
Console changes {#console-changes-27}
Enabled seamless access to SQL console for admin users
Changed default role for new invitees to "Administrator"
Added onboarding survey
Reliability and performance {#reliability-and-performance-3}
Added retry logic for longer running insert queries to recover in the event of network failures
Improved read performance of cold reads
Integrations changes {#integrations-changes-26}
The
Metabase plugin
got a long-awaited v0.9.1 major update. Now it is compatible with the latest Metabase version and has been thoroughly tested against ClickHouse Cloud.
December 6, 2022 - General availability {#december-6-2022---general-availability}
ClickHouse Cloud is now production-ready with SOC2 Type II compliance, uptime SLAs for production workloads, and public status page. This release includes major new capabilities like AWS Marketplace integration, SQL console - a data exploration workbench for ClickHouse users, and ClickHouse Academy - self-paced learning in ClickHouse Cloud. Learn more in this
blog
.
Production-ready {#production-ready}
SOC2 Type II compliance (details in
blog
and
Trust Center
)
Public
Status Page
for ClickHouse Cloud
Uptime SLA available for production use cases
Availability on
AWS Marketplace
Major new capabilities {#major-new-capabilities}
Introduced SQL console, the data exploration workbench for ClickHouse users | {"source_file": "01_changelog.md"} | [
-0.09110479801893234,
-0.016996165737509727,
-0.05802353844046593,
0.001010856474749744,
-0.03408895805478096,
-0.022693034261465073,
-0.021012108772993088,
0.04520302265882492,
-0.057737085968256,
0.019493266940116882,
-0.03994189575314522,
0.06776741147041321,
0.06482521444559097,
-0.037... |
dfcd7e5d-4906-464f-87f6-49eb5a9e69fb | Availability on
AWS Marketplace
Major new capabilities {#major-new-capabilities}
Introduced SQL console, the data exploration workbench for ClickHouse users
Launched
ClickHouse Academy
, self-paced learning in ClickHouse Cloud
Pricing and metering changes {#pricing-and-metering-changes}
Extended trial to 30 days
Introduced fixed-capacity, low-monthly-spend Development Services, well-suited for starter projects and development/staging environments
Introduced new reduced pricing on Production Services, as we continue to improve how ClickHouse Cloud operates and scales
Improved granularity and fidelity when metering compute
Integrations changes {#integrations-changes-27}
Enabled support for ClickHouse Postgres / MySQL integration engines
Added support for SQL user-defined functions (UDFs)
Advanced Kafka Connect sink to Beta status
Improved Integrations UI by introducing rich meta-data about versions, update status, and more
Console changes {#console-changes-28}
Multi-factor authentication support in the cloud console
Improved cloud console navigation for mobile devices
Documentation changes {#documentation-changes}
Introduced a dedicated
documentation
section for ClickHouse Cloud
Bug fixes {#bug-fixes-5}
Addressed known issue where restore from backup did not always work due to dependency resolution
November 29, 2022 {#november-29-2022}
This release brings SOC2 Type II compliance, updates the ClickHouse version to 22.11, and improves a number of ClickHouse clients and integrations.
General changes {#general-changes-4}
Reached SOC2 Type II compliance (details in
blog
and
Trust Center
)
Console changes {#console-changes-29}
Added an "Idle" status indicator to show that a service has been automatically paused
ClickHouse 22.11 version upgrade {#clickhouse-2211-version-upgrade}
Added support for Hudi and DeltaLake table engines and table functions
Improved recursive directory traversal for S3
Added support for composite time interval syntax
Improved insert reliability with retries on insert
See the
detailed 22.11 changelog
for the complete list of changes
Integrations {#integrations-1}
Python client: v3.11 support, improved insert performance
Go client: fix DateTime and Int64 support
JS client: support for mutual SSL authentication
dbt-clickhouse: support for DBT v1.3
Bug fixes {#bug-fixes-6}
Fixed a bug that showed an outdated ClickHouse version after an upgrade
Changing grants for the "default" account no longer interrupts sessions
Newly created non-admin accounts no longer have system table access by default
Known issues in this release {#known-issues-in-this-release}
Restore from backup may not work due to dependency resolution
November 17, 2022 {#november-17-2022} | {"source_file": "01_changelog.md"} | [
-0.03807844966650009,
-0.09278018772602081,
-0.00041863086516968906,
0.012813492678105831,
0.008410259149968624,
0.02424120157957077,
-0.07321731001138687,
-0.023501139134168625,
-0.06374029815196991,
0.07024668157100677,
-0.014497397467494011,
0.014223084785044193,
0.029088011011481285,
-... |
4cfe0fc5-6756-4093-928c-835a0302f2b1 | Known issues in this release {#known-issues-in-this-release}
Restore from backup may not work due to dependency resolution
November 17, 2022 {#november-17-2022}
This release enables dictionaries from local ClickHouse table and HTTP sources, introduces support for the Mumbai region, and improves the cloud console user experience.
General changes {#general-changes-5}
Added support for
dictionaries
from local ClickHouse table and HTTP sources
Introduced support for the Mumbai
region
Console changes {#console-changes-30}
Improved billing invoice formatting
Streamlined user interface for payment method capture
Added more granular activity logging for backups
Improved error handling during file upload
Bug fixes {#bug-fixes-7}
Fixed a bug that could lead to failing backups if there were single large files in some parts
Fixed a bug where restores from backup did not succeed if access list changes were applied at the same time
Known issues {#known-issues}
Restore from backup may not work due to dependency resolution
November 3, 2022 {#november-3-2022}
This release removes read & write units from pricing (see the
pricing page
for details), updates the ClickHouse version to 22.10, adds support for higher vertical scaling for self-service customers, and improves reliability through better defaults.
General changes {#general-changes-6}
Removed read/write units from the pricing model
Configuration changes {#configuration-changes-2}
The settings
allow_suspicious_low_cardinality_types
,
allow_suspicious_fixed_string_types
and
allow_suspicious_codecs
(default is false) cannot be changed by users anymore for stability reasons.
Console changes {#console-changes-31}
Increased the self-service maximum for vertical scaling to 720GB memory for paying customers
Improved the restore from backup workflow to set IP Access List rules and password
Introduced waitlists for GCP and Azure in the service creation dialog
Improved error handling during file upload
Improved workflows for billing administration
ClickHouse 22.10 version upgrade {#clickhouse-2210-version-upgrade}
Improved merges on top of object stores by relaxing the "too many parts" threshold in the presence of many large parts (at least 10 GiB). This enables up to petabytes of data in a single partition of a single table.
Improved control over merging with the
min_age_to_force_merge_seconds
setting, to merge after a certain time threshold.
Added MySQL-compatible syntax to reset settings
SET setting_name = DEFAULT
.
Added functions for Morton curve encoding, Java integer hashing, and random number generation.
See the
detailed 22.10 changelog
for the complete list of changes.
October 25, 2022 {#october-25-2022} | {"source_file": "01_changelog.md"} | [
-0.10063684731721878,
-0.0034238200169056654,
0.006731714587658644,
-0.017722278833389282,
-0.0006868423661217093,
0.01040982361882925,
-0.06840655207633972,
-0.016742493957281113,
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0.09887564927339554,
0.029294075444340706,
0.04570474475622177,
-0.03487758710980415,
-... |
6d8eadab-f137-47eb-b06f-e0a99fada415 | See the
detailed 22.10 changelog
for the complete list of changes.
October 25, 2022 {#october-25-2022}
This release significantly lowers compute consumption for small workloads, lowers compute pricing (see
pricing
page for details), improves stability through better defaults, and enhances the Billing and Usage views in the ClickHouse Cloud console.
General changes {#general-changes-7}
Reduced minimum service memory allocation to 24G
Reduced service idle timeout from 30 minutes to 5 minutes
Configuration changes {#configuration-changes-3}
Reduced max_parts_in_total from 100k to 10k. The default value of the
max_parts_in_total
setting for MergeTree tables has been lowered from 100,000 to 10,000. The reason for this change is that we observed that a large number of data parts is likely to cause a slow startup time of services in the cloud. A large number of parts usually indicates a choice of too granular partition key, which is typically done accidentally and should be avoided. The change of default will allow the detection of these cases earlier.
Console changes {#console-changes-32}
Enhanced credit usage details in the Billing view for trial users
Improved tooltips and help text, and added a link to the pricing page in the Usage view
Improved workflow when switching options for IP filtering
Added resend email confirmation button to the cloud console
October 4, 2022 - Beta {#october-4-2022---beta}
ClickHouse Cloud began its public Beta on October 4th, 2022. Learn more in this
blog
.
The ClickHouse Cloud version is based on ClickHouse core v22.10. For a list of compatible features, refer to the
Cloud Compatibility
guide. | {"source_file": "01_changelog.md"} | [
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0.0039211539551615715,
0.08241716027259827,
-0.04641380161046982,
-0.0325130... |
b81b456d-6a25-4d4f-8c7b-a6d228e449f8 | sidebar_label: 'ClickHouse Cloud billing compliance'
slug: /manage/clickhouse-cloud-billing-compliance
title: 'ClickHouse Cloud billing compliance'
description: 'Page describing ClickHouse Cloud billing compliance'
keywords: ['billing compliance', 'pay-as-you-go']
doc_type: 'guide'
import billing_compliance from '@site/static/images/cloud/manage/billing_compliance.png';
import Image from '@theme/IdealImage';
ClickHouse Cloud billing compliance
Billing compliance {#billing-compliance}
Your use of ClickHouse Cloud requires your organization to have an active and
valid billing method configured. After your 30 day trial ends or your trial
credits are depleted, whichever occurs first, you have the following billing
options to continue using ClickHouse Cloud:
| Billing option | Description |
|------------------------------------------------------|-----------------------------------------------------------------------------------------|
|
Direct PAYG
| Add a valid credit card to your organization to Pay-As-You-Go |
|
Marketplace PAYG
| Set up a Pay-As-You-Go subscription via a supported cloud marketplace provider |
|
Committed spend contract
| Enter into a committed spend contract directly or through a supported cloud marketplace |
If your trial ends and no billing option has been configured for your organization,
all your services will be stopped. If a billing method still has not been
configured after two weeks, all your data will be deleted.
ClickHouse charges for services at the organization level. If we are ever unable
to process a payment using your current billing method, you must update it to one
of the three options listed above to avoid service disruption. See below for more
details about payment compliance based on your chosen billing method.
Pay-as-you-go billing with a credit card {#direct-payg}
You can pay for your ClickHouse Cloud usage monthly in arrears using a credit card.
To add a credit card, follow these
instructions
.
Your monthly billing cycle for ClickHouse begins on the day the organization tier
(Basic, Scale, or Enterprise) is selected, and the first service is created within
the organization.
The credit card on file normally will be charged at the end of your monthly
billing cycle, but payment charges will be accelerated if the intracycle amount
due reaches $10,000 USD (more info on payment thresholds
here
).
The credit card on file must be valid, not expired, and have enough available
credit to cover your invoice total. If, for any reason, we are unable to charge
the full amount due, the following unpaid invoice restrictions will immediately
apply:
You will only be able to scale up to 120 GiB per replica
You will not be able to start your services if stopped | {"source_file": "06_billing_compliance.md"} | [
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cf32a860-0048-4277-a2f8-7d7f5b2adf25 | You will only be able to scale up to 120 GiB per replica
You will not be able to start your services if stopped
You will not be able to start or create new services
We will attempt to process payment using the organization's configured billing
method for up to 30 days. If payment is not successful after 14 days, all services
within the organization will be stopped. If payment is still not received by the
end of this 30 day period and we have not granted an extension, all data and
services associated with your organization will be deleted.
Cloud marketplace pay-as-you-go billing {#cloud-marketplace-payg}
Pay-As-You-Go billing can also be configured to charge an organization through one of our supported cloud marketplaces
(AWS, GCP, or Azure). To sign up for Marketplace PAYG billing, follow these
instructions
.
Similar to billing via Direct PAYG, your monthly billing cycle with ClickHouse
under Marketplace PAYG begins on the day the organization tier (Basic, Scale,
or Enterprise) is selected and the first service is created within the
organization.
However, because of the requirements of the marketplaces, we report the charges
for your Pay-As-You-Go usage on an hour-by-hour basis. Note that you will be
invoiced according to the terms of your agreement with that marketplace - typically
on a calendar-month billing cycle.
As an example, if you create your first organization service on January 18, your
first billing usage cycle in ClickHouse Cloud will run from January 18 until the
end of the day on February 17. However, you may receive your first invoice from
the cloud marketplace at the beginning of the month of February.
However, if your PAYG marketplace subscription is canceled or fails to renew
automatically, billing will fall back to the credit card on file for the
organization, if any. To add a credit card, please
contact support
for help. If a valid credit card has not been provided, the same unpaid invoice
restrictions outlined above for
Direct PAYG
will apply - this
includes service suspension and eventual data deletion.
Committed contract billing {#committed-spend-contract}
You may purchase credits for your organization through a committed contract by:
Contacting sales to buy credits directly, with payment options including ACH
or wire transfer. Payment terms will be set forth in the applicable order form.
Contacting sales to buy credits through a subscription on one of our supported
cloud marketplaces (AWS, GCP, or Azure). Fees will be reported to the applicable
marketplace upon acceptance of the private offer and thereafter in accordance
with the offer terms, but you will be invoiced according to the terms of your
agreement with that marketplace. To pay through a marketplace, follow these
instructions
. | {"source_file": "06_billing_compliance.md"} | [
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0.0323... |
05860a41-d62b-44c9-a464-c49f4240b636 | Credits applied to an organization (e.g. through committed contracts or refunds) are
available for your use for the term specified in the order form or accepted private
offer.
Credits are consumed starting on the day credit was granted in billing periods
based on the date the first organization tier (Basic, Scale, or Enterprise) is
selected.
If an organization is
not
on a cloud marketplace committed contract and runs
out of credits or the credits expire, the organization will automatically switch
to Pay-As-You-Go (PAYG) billing. In this case, we will attempt to process payment
using the credit card on file for the organization, if any.
If an organization
is
on a cloud marketplace committed contract and runs out
of credits, it will also automatically switch to PAYG billing via the same
marketplace for the remainder of the subscription. However, if the subscription
is not renewed and expires, we will then attempt to process payment using the
credit card on file for the organization, if any.
In either scenario, if we are unable to charge the configured credit card, the
unpaid invoice restrictions outlined above for
Pay-as-you-go (PAYG)
billing with a credit card will apply—this includes the suspension of services.
For more details on moving from your committed contract to PAYG billing, please refer to the “Overconsumption” section in our
Terms and Conditions
.
However, for committed contract customers, we will contact you regarding any
unpaid invoices before initiating data deletion. Data is not automatically
deleted after any period of time.
If you’d like to add additional credits before your existing ones expire or are
depleted, please
contact us
.
How to pay using a credit card {#add-credit-card}
Go to the Billing section in the ClickHouse Cloud UI and click the 'Add Credit Card'
button (shown below) to complete the setup. If you have any questions, please
contact support
for help.
How to pay via marketplaces {#marketplace-payg}
If you want to pay through one of our supported marketplaces (AWS, GCP, or Azure),
you can follow the steps
here
for help.
For any questions related specifically to cloud marketplace billing, please
contact the cloud service provider directly.
Helpful links for resolving issues with marketplace billing:
*
AWS Billing FAQs
*
GCP Billing FAQs
*
Azure Billing FAQs | {"source_file": "06_billing_compliance.md"} | [
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0.005... |
3a513023-e304-4abc-b398-4d7cc97f468d | sidebar_label: 'Payment thresholds'
slug: /cloud/billing/payment-thresholds
title: 'Payment thresholds'
description: 'Payment thresholds and automatic invoicing for ClickHouse Cloud.'
keywords: ['billing', 'payment thresholds', 'automatic invoicing', 'invoice']
doc_type: 'guide'
Payment thresholds
When your amount due in a billing period for ClickHouse Cloud reaches $10,000 USD or the equivalent value, your payment method will be automatically charged. A failed charge will result in the suspension or termination of your services after a grace period.
:::note
This payment threshold does not apply to customers who have a committed spend contract or other negotiated contractual agreement with ClickHouse.
:::
If your organization reaches 90% of the payment threshold and is on-track to exceed the payment threshold mid-period, the billing email associated with the organization will receive an email notification. You will also receive an email notification as well as an invoice when you exceed the payment threshold.
These payment thresholds can be adjusted below $10,000 as requested by customers or by the ClickHouse Finance team. If you have any questions, please contact support@clickhouse.com for more details. | {"source_file": "05_payment-thresholds.md"} | [
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fb9944a2-3991-46e0-a2b7-7ee3c6056ec2 | sidebar_label: 'Overview'
slug: /cloud/manage/billing/overview
title: 'Pricing'
description: 'Overview page for ClickHouse Cloud pricing'
doc_type: 'reference'
keywords: ['ClickHouse Cloud', 'pricing', 'billing', 'cloud costs', 'compute pricing']
For pricing information, see the
ClickHouse Cloud Pricing
page.
ClickHouse Cloud bills based on the usage of compute, storage,
data transfer
(egress over the internet and cross-region), and
ClickPipes
.
To understand what can affect your bill, and ways that you can manage your spend, keep reading.
Amazon Web Services (AWS) example {#amazon-web-services-aws-example}
:::note
- Prices reflect AWS us-east-1 pricing.
- Explore applicable data transfer and ClickPipes charges
here
.
:::
Basic: from $66.52 per month {#basic-from-6652-per-month}
Best for: Departmental use cases with smaller data volumes that do not have hard reliability guarantees.
Basic tier service
- 1 replica x 8 GiB RAM, 2 vCPU
- 500 GB of compressed data
- 500 GB of backup of data
- 10 GB of public internet egress data transfer
- 5 GB of cross-region data transfer
Pricing breakdown for this example:
Active 6 hours a day
Active 12 hours a day
Active 24 hours a day
Compute
\$39.91
\$79.83
\$159.66
Storage
\$25.30
\$25.30
\$25.30
Public internet egress data transfer
\$1.15
\$1.15
\$1.15
Cross-region data transfer
\$0.16
\$0.16
\$0.16
Total
\$66.52
\$106.44
\$186.27
Scale (always-on, auto-scaling): from $499.38 per month {#scale-always-on-auto-scaling-from-49938-per-month}
Best for: workloads requiring enhanced SLAs (2+ replica services), scalability, and advanced security.
Scale tier service
- Active workload ~100% time
- Auto-scaling maximum configurable to prevent runaway bills
- 100 GB of public internet egress data transfer
- 10 GB of cross-region data transfer
Pricing breakdown for this example:
Example 1
Example 2
Example 3
Compute
2 replicas x 8 GiB RAM, 2 vCPU
\$436.95
2 replicas x 16 GiB RAM, 4 vCPU
\$873.89
3 replicas x 16 GiB RAM, 4 vCPU
\$1,310.84
Storage
1 TB of data + 1 backup
\$50.60
2 TB of data + 1 backup
\$101.20
3 TB of data + 1 backup
\$151.80
Public internet egress data transfer
\$11.52
\$11.52
\$11.52
Cross-region data transfer
\$0.31
\$0.31
\$0.31
Total
\$499.38
\$986.92
\$1,474.47
Enterprise: Starting prices vary {#enterprise-starting-prices-vary}
Best for: large scale, mission critical deployments that have stringent security and compliance needs
Enterprise tier service
- Active workload ~100% time
- 1 TB of public internet egress data transfer
- 500 GB of cross-region data transfer
Example 1
Example 2
Example 3
Compute
2 replicas x 32 GiB RAM, 8 vCPU
\$2,285.60
2 replicas x 64 GiB RAM, 16 vCPU
\$4,571.19
2 x 120 GiB RAM, 30 vCPU
\$8,570.99
Storage
5 TB + 1 backup
\$253.00 | {"source_file": "01_billing_overview.md"} | [
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0.000130309141241014,
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0.07694165408611298,
-0.022809069603681564,
-0.03207426145672798,
0.03613492101430893,
... |
061b1cf1-4670-404a-80e4-ded8c3e3ac0d | Example 3
Compute
2 replicas x 32 GiB RAM, 8 vCPU
\$2,285.60
2 replicas x 64 GiB RAM, 16 vCPU
\$4,571.19
2 x 120 GiB RAM, 30 vCPU
\$8,570.99
Storage
5 TB + 1 backup
\$253.00
10 TB + 1 backup
\$506.00
20 TB + 1 backup
\$1,012.00
Public internet egress data transfer
\$115.20
\$115.20
\$115.20
Cross-region data transfer
\$15.60
\$15.60
\$15.60
Total
\$2,669.40
\$5,207.99
\$9,713.79
Frequently asked questions {#faqs}
What is a ClickHouse Credit (CHC)? {#what-is-chc}
A ClickHouse Credit is a unit of credit toward Customer's usage of ClickHouse Cloud equal to one (1) US dollar, to be applied based on ClickHouse's then-current published price list.
:::note
If you are being billed through Stripe then you will see that 1 CHC is equal to \$0.01 USD on your Stripe invoice. This is to allow accurate billing on Stripe due to their limitation on not being able to bill fractional quantities of our standard SKU of 1 CHC = \$1 USD.
:::
Where can I find legacy pricing? {#find-legacy-pricing}
Legacy pricing information can be found
here
.
How is compute metered? {#how-is-compute-metered}
ClickHouse Cloud meters compute on a per-minute basis, in 8G RAM increments.
Compute costs will vary by tier, region, and cloud service provider.
How is storage on disk calculated? {#how-is-storage-on-disk-calculated}
ClickHouse Cloud uses cloud object storage and usage is metered on the compressed size of data stored in ClickHouse tables.
Storage costs are the same across tiers and vary by region and cloud service provider.
Do backups count toward total storage? {#do-backups-count-toward-total-storage}
Storage and backups are counted towards storage costs and billed separately.
All services will default to one backup, retained for a day.
Users who need additional backups can do so by configuring additional
backups
under the settings tab of the Cloud console.
How do I estimate compression? {#how-do-i-estimate-compression}
Compression can vary from dataset to dataset.
How much it varies is dependent on how compressible the data is in the first place (number of high vs. low cardinality fields),
and how the user sets up the schema (using optional codecs or not, for instance).
It can be on the order of 10x for common types of analytical data, but it can be significantly lower or higher as well.
See the
optimizing documentation
for guidance and this
Uber blog
for a detailed logging use case example.
The only practical way to know exactly is to ingest your dataset into ClickHouse and compare the size of the dataset with the size stored in ClickHouse.
You can use the query:
sql title="Estimating compression"
SELECT formatReadableSize(total_bytes)
FROM system.tables
WHERE name = <your table name> | {"source_file": "01_billing_overview.md"} | [
-0.06811971217393875,
-0.021595317870378494,
-0.08660479635000229,
-0.010718734003603458,
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0.006344348192214966,
0.032917533069849014,
0.023604316636919975,
0.05173986032605171,
0.054171398282051086,
-0.016917511820793152,
-0.10966175049543381,
0.07071395963430405,
-0... |
6a0285ce-f2d5-4c92-8259-ddaf7c276939 | You can use the query:
sql title="Estimating compression"
SELECT formatReadableSize(total_bytes)
FROM system.tables
WHERE name = <your table name>
What tools does ClickHouse offer to estimate the cost of running a service in the cloud if I have a self-managed deployment? {#what-tools-does-clickhouse-offer-to-estimate-the-cost-of-running-a-service-in-the-cloud-if-i-have-a-self-managed-deployment}
The ClickHouse query log captures
key metrics
that can be used to estimate the cost of running a workload in ClickHouse Cloud.
For details on migrating from self-managed to ClickHouse Cloud please refer to the
migration documentation
, and contact
ClickHouse Cloud support
if you have further questions.
What billing options are available for ClickHouse Cloud? {#what-billing-options-are-available-for-clickhouse-cloud}
ClickHouse Cloud supports the following billing options:
Self-service monthly (in USD, via credit card).
Direct-sales annual / multi-year (through pre-paid "ClickHouse Credits", in USD, with additional payment options).
Through the AWS, GCP, and Azure marketplaces (either pay-as-you-go (PAYG) or commit to a contract with ClickHouse Cloud through the marketplace).
:::note
ClickHouse Cloud credits for PAYG are invoiced in \$0.01 units, allowing us to charge customers for partial ClickHouse credits based on their usage. This differs from committed spend ClickHouse credits, which are purchased in advance in whole \$1 units.
:::
Can I delete my credit card? {#can-i-delete-my-credit-card}
You can’t remove a credit card in the Billing UI, but you can update it anytime. This helps ensure your organization always has a valid payment method. If you need to remove your credit card, please contact
ClickHouse Cloud support
for help.
How long is the billing cycle? {#how-long-is-the-billing-cycle}
Billing follows a monthly billing cycle and the start date is tracked as the date when the ClickHouse Cloud organization was created.
If I have an active PAYG marketplace subscription and then sign a committed contract, will my committed credits be consumed first? {#committed-credits-consumed-first-with-active-payg-subscription}
Yes. Usage is consumed with the following payment methods in this order:
- Committed (prepaid) credits
- Marketplace subscription (PAYG)
- Credit card
What controls does ClickHouse Cloud offer to manage costs for Scale and Enterprise services? {#what-controls-does-clickhouse-cloud-offer-to-manage-costs-for-scale-and-enterprise-services}
Trial and Annual Commit customers are notified automatically by email when their consumption hits certain thresholds:
50%
,
75%
, and
90%
. This allows users to proactively manage their usage.
ClickHouse Cloud allows users to set a maximum auto-scaling limit on their compute via
Advanced scaling control
, a significant cost factor for analytical workloads. | {"source_file": "01_billing_overview.md"} | [
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0.07532090693712234,
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-0.0814228504896164,
0.05533451959490776,
... |
8e97e32a-b225-41e7-ae8d-7c3cbd3571dc | ClickHouse Cloud allows users to set a maximum auto-scaling limit on their compute via
Advanced scaling control
, a significant cost factor for analytical workloads.
The
Advanced scaling control
lets you set memory limits with an option to control the behavior of pausing/idling during inactivity.
What controls does ClickHouse Cloud offer to manage costs for Basic services? {#what-controls-does-clickhouse-cloud-offer-to-manage-costs-for-basic-services}
The
Advanced scaling control
lets you control the behavior of pausing/idling during inactivity. Adjusting memory allocation is not supported for Basic services.
Note that the default setting pauses the service after a period of inactivity.
If I have multiple services, do I get an invoice per service or a consolidated invoice? {#if-i-have-multiple-services-do-i-get-an-invoice-per-service-or-a-consolidated-invoice}
A consolidated invoice is generated for all services in a given organization for a billing period.
If I add my credit card and upgrade before my trial period and credits expire, will I be charged? {#if-i-add-my-credit-card-and-upgrade-before-my-trial-period-and-credits-expire-will-i-be-charged}
When a user converts from trial to paid before the 30-day trial period ends, but with credits remaining from the trial credit allowance,
we continue to draw down from the trial credits during the initial 30-day trial period, and then charge the credit card.
How can I keep track of my spending? {#how-can-i-keep-track-of-my-spending}
The ClickHouse Cloud console provides a Usage display that details usage per service. This breakdown, organized by usage dimensions, helps you understand the cost associated with each metered unit.
How do I access my invoices for my subscription to the ClickHouse Cloud service? {#how-do-i-access-my-invoice-for-my-subscription-to-the-clickhouse-cloud-service}
For direct subscriptions using a credit card:
To view your invoices, select your organization from the left-hand navigation bar in the ClickHouse Cloud UI, then go to Billing. All of your invoices will be listed under the Invoices section.
For subscriptions through a cloud marketplace:
All marketplace subscriptions are billed and invoiced by the marketplace. You can view your invoice through the respective cloud provider marketplace directly.
Why do the dates on the Usage statements not match my Marketplace Invoice? {#why-do-the-dates-on-the-usage-statements-not-match-my-marketplace-invoice}
AWS Marketplace billing follows the calendar month cycle.
For example, for usage between dates 01-Dec-2024 and 01-Jan-2025,
an invoice is generated between 3-Jan and 5-Jan-2025
ClickHouse Cloud usage statements follow a different billing cycle where usage is metered
and reported over 30 days starting from the day of sign up. | {"source_file": "01_billing_overview.md"} | [
-0.045491427183151245,
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0.05632610246539116,
0.03261706605553627,
0.04129599779844284,
-0.0016246810555458069,
-0.036... |
554b164e-2e30-4602-ab1b-3d44adcd3168 | ClickHouse Cloud usage statements follow a different billing cycle where usage is metered
and reported over 30 days starting from the day of sign up.
The usage and invoice dates will differ if these dates are not the same. Since usage statements track usage by day for a given service, users can rely on statements to see the breakdown of costs.
Are there any restrictions around the usage of prepaid credits? {#are-there-any-restrictions-around-the-usage-of-prepaid-credits}
ClickHouse Cloud prepaid credits (whether direct through ClickHouse, or via a cloud provider's marketplace)
can only be leveraged for the terms of the contract.
This means they can be applied on the acceptance date, or a future date, and not for any prior periods.
Any overages not covered by prepaid credits must be covered by a credit card payment or marketplace monthly billing.
Is there a difference in ClickHouse Cloud pricing, whether paying through the cloud provider marketplace or directly to ClickHouse? {#is-there-a-difference-in-clickhouse-cloud-pricing-whether-paying-through-the-cloud-provider-marketplace-or-directly-to-clickhouse}
There is no difference in pricing between marketplace billing and signing up directly with ClickHouse.
In either case, your usage of ClickHouse Cloud is tracked in terms of ClickHouse Cloud Credits (CHCs),
which are metered in the same way and billed accordingly.
How is compute-compute separation billed? {#how-is-compute-compute-separation-billed}
When creating a service in addition to an existing service,
you can choose if this new service should share the same data with the existing one.
If yes, these two services now form a
warehouse
.
A warehouse has the data stored in it with multiple compute services accessing this data.
As the data is stored only once, you only pay for one copy of data, though multiple services are accessing it.
You pay for compute as usual — there are no additional fees for compute-compute separation / warehouses.
By leveraging shared storage in this deployment, users benefit from cost savings on both storage and backups.
Compute-compute separation can save you a significant amount of ClickHouse Credits in some cases.
A good example is the following setup:
You have ETL jobs that are running 24/7 and ingesting data into the service. These ETL jobs do not require a lot of memory so they can run on a small instance with, for example, 32 GiB of RAM.
A data scientist on the same team that has ad hoc reporting requirements, says they need to run a query that requires a significant amount of memory - 236 GiB, however does not need high availability and can wait and rerun queries if the first run fails.
In this example you, as an administrator for the database, can do the following:
Create a small service with two replicas 16 GiB each - this will satisfy the ETL jobs and provide high availability. | {"source_file": "01_billing_overview.md"} | [
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abb008e4-666e-420d-a8f1-33412617069a | Create a small service with two replicas 16 GiB each - this will satisfy the ETL jobs and provide high availability.
For the data scientist, you can create a second service in the same warehouse with only one replica with 236 GiB. You can enable idling for this service so you will not be paying for this service when the data scientist is not using it.
Cost estimation (per month) for this example on the
Scale Tier
:
- Parent service active 24 hours day: 2 replicas x 16 GiB 4 vCPU per replica
- Child service: 1 replica x 236 GiB 59 vCPU per replica per replica
- 3 TB of compressed data + 1 backup
- 100 GB of public internet egress data transfer
- 50 GB of cross-region data transfer
Child service
active 1 hour/day
Child service
active 2 hours/day
Child service
active 4 hours/day
Compute
\$1,142.43
\$1,410.97
\$1,948.05
Storage
\$151.80
\$151.80
\$151.80
Public internet egress data transfer
\$11.52
\$11.52
\$11.52
Cross-region data transfer
\$1.56
\$1.56
\$1.56
Total
\$1,307.31
\$1,575.85
\$2,112.93
Without warehouses, you would have to pay for the amount of memory that the data engineer needs for his queries.
However, combining two services in a warehouse and idling one of them helps you save money.
ClickPipes pricing {#clickpipes-pricing}
For information on ClickPipes billing, please see the dedicated
"ClickPipes billing" section
. | {"source_file": "01_billing_overview.md"} | [
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a30bc72c-5e80-433b-8ab2-a3db7ebb6d37 | slug: /cloud/manage/billing
title: 'Billing'
description: 'Table of contents page for billing.'
keywords: ['billing', 'payment thresholds', 'trouble shooting', 'marketplace']
doc_type: 'landing-page'
This section of the documentation covers topics related to billing, and contains the following pages:
| Page | Description |
|---------------------------------------|----------------------------------------------------------------------|
|
Overview
| Pricing examples and FAQs for billing. |
|
Payment Thresholds
| Learn more about how payment thresholds work and how to adjust them. |
|
Troubleshooting Billing Issues
| Troubleshoot common billing issues. |
|
Marketplace
| Landing page for further marketplace related topics. |
https://clickhouse.com/docs/cloud/ | {"source_file": "index.md"} | [
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95a712d7-8e7b-41cd-8286-de328b86bc78 | slug: /changelogs/25.8
title: 'v25.8 Changelog for Cloud'
description: 'Fast release changelog for v25.8'
keywords: ['changelog', 'cloud']
sidebar_label: '25.8'
sidebar_position: 1
doc_type: 'changelog'
Backward incompatible changes {#backward-incompatible-changes}
JSON and data format changes {#json-and-data-format-changes}
Disable quoting 64 bit integers in JSON formats by default.
#74079
(
Pavel Kruglov
).
Infer
Array(Dynamic)
instead of unnamed
Tuple
for arrays of values with different types in JSON. To use the previous behaviour, disable setting
input_format_json_infer_array_of_dynamic_from_array_of_different_types
.
#80859
(
Pavel Kruglov
).
Write values of
Enum
type as
BYTE_ARRAY
with
ENUM
logical type in Parquet output format by default.
#84169
(
Pavel Kruglov
).
Storage and partitioning {#storage-and-partitioning}
Add support for hive partition style writes and refactor reads implementation (hive partition columns are no longer virtual).
#76802
(
Arthur Passos
).
Enable MergeTree setting
write_marks_for_substreams_in_compact_parts
by default. It significantly improves performance of subcolumns reading from newly created Compact parts. Servers with version less than 25.5 won't be able to read the new ompact parts.
#84171
(
Pavel Kruglov
).
Disallow
RENAME COLUMN
or
DROP COLUMN
involving explicitly listed columns to sum in SummingMergeTree. Closes
#81836
.
#82821
(
Alexey Milovidov
).
Function enhancements {#function-enhancements}
Introduce a new argument
unexpected_quoting_character_strategy
to the
extractKeyValuePairs
function that controls what happens when a
quoting_character
is unexpectedly found. For more details see the docs for
extractKeyValuePairs
.
#80657
(
Arthur Passos
).
Previously, the function
countMatches
would stop counting at the first empty match even if the pattern accepts it. To overcome this issue,
countMatches
now continues execution by advancing by a single character when an empty match occurs. Users who would like to retain the old behavior can enable setting
count_matches_stop_at_empty_match
.
#81676
(
Elmi Ahmadov
).
Data type improvements {#data-type-improvements}
Improve the precision of conversion from
Decimal
to
Float32
. Implement conversion from
Decimal
to
BFloat16
. Closes
#82660
.
#82823
(
Alexey Milovidov
).
Performance and resource management {#performance-and-resource-management} | {"source_file": "25_08.md"} | [
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a92d7e6f-1a68-4d43-a843-224bb7593741 | Performance and resource management {#performance-and-resource-management}
Previously,
BACKUP
queries, merges and mutations were not using server-wide throttlers for local (
max_local_read_bandwidth_for_server
and
max_local_write_bandwidth_for_server
) and remote (
max_remote_read_network_bandwidth_for_server
and
max_remote_write_network_bandwidth_for_server
) traffic, instead they were only throttled by dedicated server settings (
max_backup_bandwidth_for_server
,
max_mutations_bandwidth_for_server
and
max_merges_bandwidth_for_server
). Now, they use both types of throttlers simultaneously.
#81753
(
Sergei Trifonov
).
Added a new setting
cluster_function_process_archive_on_multiple_nodes
which increases performance of processing archives in cluster functions when set to true (by default). Should be set to
false
for compatibility and to avoid errors during upgrade to 25.7+ if using cluster functions with archives on earlier versions.
#82355
(
Kseniia Sumarokova
).
The previous
concurrent_threads_scheduler
default value was
round_robin
, which proved unfair in the presence of a high number of single-threaded queries (e.g.,
INSERT
s). This change makes a safer alternative
fair_round_robin
scheduler, the default.
#84747
(
Sergei Trifonov
).
Lazy materialization is enabled only with the analyzer to avoid maintenance without the analyzer which can have some issues (for example, when using
indexHint()
in conditions).
#83791
(
Igor Nikonov
).
Schema and SQL syntax {#schema-and-sql-syntax}
Forbid the creation of a table without insertable columns.
#81835
(
Pervakov Grigorii
).
Require backticks around identifiers with dots in default expressions to prevent them from being parsed as compound identifiers.
#83162
(
Pervakov Grigorii
).
Support PostgreSQL-style heredoc syntax:
$tag$ string contents... $tag$
, also known as dollar-quoted string literals. In previous versions, there were fewer restrictions on tags: they could contain arbitrary characters, including punctuation and whitespace. This introduces parsing ambiguity with identifiers that can also start with a dollar character. At the same time, PostgreSQL only allows word characters for tags. To resolve the problem, we now restrict heredoc tags only to contain word characters. Closes
#84731
.
#84846
(
Alexey Milovidov
).
Security and permissions {#security-and-permissions}
SYSTEM RESTART REPLICAS
will only restart replicas in the databases where you have permission to
SHOW TABLES
. Previously the query led to the wakeup of tables in the Lazy database, even without access to that database, while these tables were being concurrently dropped.
#83321
(
Alexey Milovidov
). | {"source_file": "25_08.md"} | [
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-0.0... |
63bb3057-b5dc-452d-a75f-cd0869340861 | Functions
azureBlobStorage
,
deltaLakeAzure
, and
icebergAzure
have been updated to properly validate
AZURE
permissions. All cluster-variant functions (
-Cluster
functions) now verify permissions against their corresponding non-clustered counterparts. Additionally, the
icebergLocal
and
deltaLakeLocal
functions now enforce
FILE
permission checks.
#84938
([Nikita Mikhaylov](https://github.com/nikitamikhaylov
New features {#new-feature}
Data types {#data-types}
Add new data types:
Time
([H]HH:MM:SS)
and
Time64
([H]HH:MM:SS[.fractional])
, and some basic cast functions and functions to interact with other data types. Added settings for compatibility with a legacy function
ToTime
.
#81217
(
Yarik Briukhovetskyi
).
Functions {#functions}
Add
NumericIndexedVector
, a new vector data-structure backed by bit-sliced, roaring-bitmap compression, together with more than 20 functions for building, analysing and point-wise arithmetic. Can cut storage and speed up joins, filters and aggregations on sparse data. Implements
#70582
and
"Large-Scale Metric Computation in Online Controlled Experiment Platform" paper
by T. Xiong and Y. Wang from VLDB 2024.
#74193
(
FriendLey
).
Add financial functions:
financialInternalRateOfReturnExtended
(
XIRR
),
financialInternalRateOfReturn
(
IRR
),
financialNetPresentValueExtended
(
XNPV
),
financialNetPresentValue
(
NPV
).
#81599
(
Joanna Hulboj
).
Add the geospatial functions
polygonIntersectsCartesian
and
polygonIntersectsSpherical
to check if two polygons intersect.
#81882
(
Paul Lamb
).
Support
lag
and
lead
window functions. Closes
#9887
.
#82108
(
Dmitry Novik
).
Add functions
colorSRGBToOkLCH
and
colorOkLCHToSRGB
for converting colours between the sRGB and OkLCH colour spaces.
#83679
(
Fgrtue
).
Users can now do case-insensitive JSON key lookups using
JSONExtractCaseInsensitive
(and other variants of
JSONExtract
).
#83770
(
Alistair Evans
).
Add a new function
nowInBlock64
.
#84178
(
Halersson Paris
).
Add function
dateTimeToUUIDv7
to convert a DateTime value to a UUIDv7. Example usage:
SELECT dateTimeToUUIDv7(toDateTime('2025-08-15 18:57:56'))
returns
0198af18-8320-7a7d-abd3-358db23b9d5c
.
#84319
(
samradovich
).
Add
timeSeriesDerivToGrid
and
timeSeriesPredictLinearToGrid
aggregate functions to re-sample data to a time grid defined by the specified start timestamp, end timestamp, and step; calculates PromQL-like
deriv
and
predict_linear
, respectively.
#84328
(
Stephen Chi
).
Add
timeSeriesRange
and
timeSeriesFromGrid
functions.
#85435
(
Vitaly Baranov
).
System tables {#system-tables}
Add a
system.dead_letter_queue
table to keep erroneous incoming messages from engines like Kafka.
#68873
(
Ilya Golshtein
).
Add
system.zookeeper_connection_log
system table to store historical information about ZooKeeper connections.
#79494
(
János Benjamin Antal
). | {"source_file": "25_08.md"} | [
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0.021944459527730942,
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0.0485506... |
9e8fba38-2c05-48e1-8ab9-bcfbac27746e | Add
system.zookeeper_connection_log
system table to store historical information about ZooKeeper connections.
#79494
(
János Benjamin Antal
).
Added a new system table
system.codecs
to introspect the available codecs. (issue
#81525
).
#81600
(
Jimmy Aguilar Mena
).
Introduction of
system.completions
table. Closes
#81889
.
#83833
(
|2ustam
).
Iceberg and DeltaLake {#iceberg-and-deltalake}
Support complex types in iceberg schema evolution.
#73714
(
scanhex12
).
Introduce Iceberg writes for
insert
queries.
#82692
(
scanhex12
).
Support positional deletes for the Iceberg table engine.
#83094
(
Daniil Ivanik
).
Read iceberg data files by field ids. Closes
#83065
.
#83653
(
scanhex12
).
Iceberg writes for create. Closes
#83927
.
#83983
(
scanhex12
).
Writes for Glue catalogs.
#84136
(
scanhex12
).
Writes for Iceberg Rest catalogs.
#84684
(
scanhex12
).
Merge all iceberg position delete files into data files. This will reduce amount and sizes of parquet files in iceberg storage. Syntax:
OPTIMIZE TABLE table_name
.
#85250
(
scanhex12
).
Support
DROP TABLE
for iceberg (Removing from REST/Glue catalogs + removing metadata about the table).
#85395
(
scanhex12
).
Support
ALTER DELETE
mutations for iceberg in merge-on-read format.
#85549
(
scanhex12
).
Support writes into DeltaLake. Closes
#79603
.
#85564
(
Kseniia Sumarokova
).
Write more iceberg statistics (column sizes, lower and upper bounds) in metadata (manifest entries) for min-max pruning.
#85746
(
scanhex12
).
Support add/drop/modify columns in iceberg for simple types.
#85769
(
scanhex12
).
MergeTree and storage {#mergetree-and-storage}
All tables now support the
_table
virtual column, not only Merge type tables.
#63665
(
Xiaozhe Yu
).
Add SZ3 as a lossy yet error-bounded compression codec for columns of type
Float32
and
Float64
.
#67161
(
scanhex12
).
Added support for lightweight updates for
MergeTree
-family tables. Lightweight updates can be used by a new syntax:
UPDATE <table> SET col1 = val1, col2 = val2, ... WHERE <condition>
. Added implementation of lightweight deletes via lightweight updates which can be enabled by setting
lightweight_delete_mode = 'lightweight_update'
.
#82004
(
Anton Popov
).
Support
_part_granule_offset
virtual column in MergeTree-family tables. This column indicates the zero-based index of the granule/mark each row belongs to within its data part. This addresses
#79572
.
#82341
(
Amos Bird
).
Protocol and client Support {#protocol-and-client-support}
Implement support for
ArrowFlight RPC
protocol by adding the
arrowflight
table engine.
#74184
(
zakr600
).
Add PostgreSQL protocol
COPY
command support.
#74344
(
scanhex12
).
Support C# client for mysql protocol. This closes
#83992
.
#84397
(
scanhex12
).
Force secure connection for
mysql_port
and
postgresql_port
.
#82962
(
Shaohua Wang
). | {"source_file": "25_08.md"} | [
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0.002235859865322709,
-0.049831... |
27dfaea3-d5c5-4b25-bb9d-54342a59daf9 | Support C# client for mysql protocol. This closes
#83992
.
#84397
(
scanhex12
).
Force secure connection for
mysql_port
and
postgresql_port
.
#82962
(
Shaohua Wang
).
SQL and query features {#sql-and-query-features}
Support
DESCRIBE SELECT
in addition to
DESCRIBE (SELECT ...)
.
#82947
(
Yarik Briukhovetskyi
).
Support writing
USE DATABASE {name}
.
#81307
(
Yarik Briukhovetskyi
).
Reading from projections is implemented for parallel replicas. A new setting
parallel_replicas_support_projection
has been added to control whether projection support is enabled. To simplify the implementation, support for projection is only enabled when
parallel_replicas_local_plan
is active.
#82807
(
zoomxi
).
Formats {#formats}
Add
format_schema_source
setting which defines the source of
format_schema
.
#80874
(
Tuan Pham Anh
).
Added
Hash
as a new output format. It calculates a single hash value for all columns and rows of the result. This is useful for calculating a "fingerprint" of the result, for example, in use cases where data transfer is a bottleneck. Example:
SELECT arrayJoin(['abc', 'def']), 42 FORMAT Hash
returns
e5f9e676db098fdb9530d2059d8c23ef
.
#84607
(
Robert Schulze
).
Server configuration and workload management {#server-configuration-and-workload-management}
Server setting
cpu_slot_preemption
enables preemptive CPU scheduling for workloads and ensures max-min fair allocation of CPU time among workloads. New workload settings for CPU throttling are added:
max_cpus
,
max_cpu_share
and
max_burst_cpu_seconds
.
#80879
(
Sergei Trifonov
).
The workload setting
max_waiting_queries
is now supported. It can be used to limit the size of the query queue. If the limit is reached, all subsequent queries will be terminated with the
SERVER_OVERLOADED
error.
#81250
(
Oleg Doronin
).
Drop TCP connection after configured number of queries or time threshold. Resolves
#68000
.
#81472
(
Kenny Sun
).
Cloud storage {#cloud-storage}
Add
extra_credentials
to
AzureBlobStorage
to authenticate with
client_id
and
tenant_id
.
#84235
(
Pablo Marcos
).
Keeper {#keeper}
Add the ability to set up arbitrary watches in Keeper Multi queries.
#84964
(
Mikhail Artemenko
).
Support partially aggregated metrics.
#85328
(
Mikhail Artemenko
).
Experimental features {#experimental-features}
Table engines and table functions {#table-engines-and-table-functions}
Add Ytsaurus table engine and table function.
#77606
(
MikhailBurdukov
).
Text index improvements {#text-index-improvements}
Add functions
searchAny
and
searchAll
which are general purpose tools to search text indexes.
#80641
(
Elmi Ahmadov
).
The text index now supports
string
tokenizer.
#81752
(
Elmi Ahmadov
). | {"source_file": "25_08.md"} | [
-0.034041840583086014,
-0.038878340274095535,
-0.09877842664718628,
-0.04534575715661049,
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-0.032268695533275604,
0.025608904659748077,
-0.004434854257851839,
-0.051408715546131134,
0.08874724060297012,
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0.0067406706511974335,
0.1648653745651245,
... |
f449661a-c7b2-4165-a5be-5f8763760785 | The text index now supports
string
tokenizer.
#81752
(
Elmi Ahmadov
).
Changed the default index granularity value for
text
indexes to 64. This improves the expected performance for the average test query in internal benchmarks.
#82162
(
Jimmy Aguilar Mena
).
The 256-bit bitmap stores the outgoing labels of a state ordered, but outgoing states are saved into disk in the order they appear in the hash table. Therefore, a label would point to a wrong next state while reading from disk.
#82783
(
Elmi Ahmadov
).
Currently, FST tree is saved into disk uncompressed. This could lead to slow performance or higher I/O bandwidth while both writing and reading into/from disk.
#83093
(
Elmi Ahmadov
).
Feature maturity updates {#feature-maturity-updates}
Moved catalog to beta.
#85848
(
Melvyn Peignon
).
Lightweight updates moved to the beta stage from experimental.
#85952
(
Anton Popov
).
Performance improvements {#performance-improvements}
Query execution and aggregation {#query-execution-and-aggregation}
Trivial optimization for
-If
aggregate function combinator.
#78454
(
李扬
).
Added new logic (controlled by the setting
enable_producing_buckets_out_of_order_in_aggregation
, enabled by default) that allows sending some buckets out of order during memory-efficient aggregation. When some aggregation buckets take significantly longer to merge than others, it improves performance by allowing the initiator to merge buckets with higher bucket id-s in the meantime. The downside is potentially higher memory usage (shouldn't be significant).
#80179
(
Nikita Taranov
).
Make the pipeline after the
TOTALS
step multithreaded.
#80331
(
UnamedRus
).
When the aggregation query contains only a single
COUNT()
function on a
NOT NULL
column, the aggregation logic is fully inlined during hash table probing. This avoids allocating and maintaining any aggregation state, significantly reducing memory usage and CPU overhead. This partially addresses
#81982
.
#82104
(
Amos Bird
).
Calculate serialized key columnarly when group by multiple string or number columns.
#83884
(
李扬
).
Implement
addManyDefaults
for
-If
combinators.
#83870
(
Raúl Marín
).
JOIN optimizations {#join-optimizations}
Add new setting
min_joined_block_size_rows
(analogous to
min_joined_block_size_bytes
; defaults to 65409) to control the minimum block size (in rows) for JOIN input and output blocks (if the join algorithm supports it). Small blocks will be squashed.
#81886
(
Nikita Taranov
).
Performance of
HashJoin
optimised by removing the additional loop over hash maps in the typical case of only one key column, also
null_map
and
join_mask
checks are eliminated when they're always
true
/
false
.
#82308
(
Nikita Taranov
). | {"source_file": "25_08.md"} | [
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0.0053574214689433575,
-0.03730025142431259,
0.07703253626823425,
-0.010256120935082436,
-0... |
434be590-d322-4c8a-a9fb-151c3d36f1df | The optimizations for
null_map
and
JoinMask
from
#82308
were applied to the case of JOIN with multiple disjuncts. Also, the
KnownRowsHolder
data structure was optimized.
#83041
(
Nikita Taranov
).
Plain
std::vector<std::atomic_bool>
is used for join flags to avoid calculating a hash on each access to flags.
#83043
(
Nikita Taranov
).
Process
max_joined_block_rows
outside of hash JOIN main loop. Slightly better performance for ALL JOIN.
#83216
(
Nikolai Kochetov
).
Don't pre-allocate memory for result columns beforehand when
HashJoin
uses
lazy
output mode. It is suboptimal, especially when the number of matches is low. Moreover, we know the exact amount of matches after joining is done, so we can preallocate more precisely.
#83304
(
Nikita Taranov
).
All
LEFT/INNER
JOINs will be automatically converted to
RightAny
if the right side is functionally determined by the join key columns (all rows have unique join key values).
#84010
(
Nikita Taranov
).
Improved performance of applying patch parts in
Join
mode.
#85040
(
Anton Popov
).
Distributed query improvements {#distributed-query-improvements}
Introduced an option to offload (de)compression and (de)serialization of blocks into pipeline threads instead of a single thread associated with a network connection. Controlled by the setting
enable_parallel_blocks_marshalling
. It should speed up distributed queries that transfer significant amounts of data between the initiator and remote nodes.
#78694
(
Nikita Taranov
).
Parallel distributed
INSERT SELECT
is enabled by default in mode where
INSERT SELECT
executed on each shard independently, see
parallel_distributed_insert_select
setting.
#80425
(
Igor Nikonov
).
Compress logs and profile events in the native protocol. On clusters with 100+ replicas, uncompressed profile events take 1..10 MB/sec, and the progress bar is sluggish on slow Internet connections. This closes
#82533
.
#82535
(
Alexey Milovidov
).
Parallel distributed
INSERT SELECT
is enabled by default in mode where INSERT SELECT executed on each shard independently, see
parallel_distributed_insert_select
setting.
#83040
(
Igor Nikonov
).
Fixed the calculation of the minimal task size for parallel replicas.
#84752
(
Nikita Taranov
).
Index improvements {#index-improvements}
Vector search queries using a vector similarity index complete with lower latency due to reduced storage reads and reduced CPU usage.
#79103
(
Shankar Iyer
).
Respect
merge_tree_min_{rows,bytes}_for_seek
in
filterPartsByQueryConditionCache
to align it with other methods filtering by indexes.
#80312
(
李扬
).
Process higher granularity min-max indexes first. Closes
#75381
.
#83798
(
Maruth Goyal
). | {"source_file": "25_08.md"} | [
0.0020193508826196194,
0.08801845461130142,
0.0073021091520786285,
-0.05716736987233162,
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0.008163279853761196,
-0.00792013667523861,
0.03354714438319206,
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0.00713910860940814,
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0.03874543309211731,
-0.019332006573677063,
-0.... |
48b53caf-d387-477a-ab68-3ec47ff44611 | Process higher granularity min-max indexes first. Closes
#75381
.
#83798
(
Maruth Goyal
).
The bloom filter index is now used for conditions like
has([c1, c2, ...], column)
, where
column
is not of an
Array
type. This improves performance for such queries, making them as efficient as the
IN
operator.
#83945
(
Doron David
).
Processes indexes in increasing order of file size. The net index ordering prioritizes minmax and vector indexes (due to simplicity and selectivity respectively), and small indexes thereafter. Within the minmax/vector indexes smaller indexes are also preferred.
#84094
(
Maruth Goyal
).
Previously, the text index data would be separated into multiple segments (each segment size by default was 256 MiB). This might reduce the memory consumption while building the text index, however this increases the space requirement on the disk and increase the query response time.
#84590
(
Elmi Ahmadov
).
Subquery optimizations {#subquery-optimizations}
Optimize the generated plan for correlated subqueries by removing redundant
JOIN
operations using equivalence classes. If there are equivalent expressions for all correlated columns,
CROSS JOIN
is not produced if
query_plan_correlated_subqueries_use_substitution
setting is enabled.
#82435
(
Dmitry Novik
).
Read only required columns in correlated subquery when it appears to be an argument of function
EXISTS
.
#82443
(
Dmitry Novik
).
Azure Blob Storage improvements {#azure-blob-storage-improvements}
azureBlobStorage
table engine now cachees and reuses managed identity authentication tokens when possible to avoid throttling.
#79860
(
Nick Blakely
).
Replace curl HTTP client with poco HTTP client for azure blob storage. Introduced multiple settings for these clients which mirror settings from S3. Introduced aggressive connect timeouts for both Azure and S3. Improved introspection into Azure profile events and metrics. New client is enabled by default, provide much better latencies for cold queries on top of Azure Blob Storage. Old
Curl
client can be returned back by setting
azure_sdk_use_native_client=false
.
#83294
(
alesapin
).
Storage engine improvements {#storage-engine-improvements}
Fix filter by key for Redis and KeeperMap storages.
#81833
(
Pervakov Grigorii
).
ATTACH PARTITION
no longer leads to the dropping of all caches.
#82377
(
Alexey Milovidov
).
Avoid holding the lock while creating storage snapshot data to reduce lock contention with high concurrent load.
#83510
(
Duc Canh Le
).
Removing temporary parts may take a while (especially with S3), and currently we do it while holding a global lock in
MergeTreeBackgroundExecutor
. When we need to restart all tables due to connection loss and we wait for background tasks to finish - tables may even stuck in readonly mode for an hour. But looks like we don't need this lock for calling
cancel
.
#84311
(
Alexander Tokmakov
). | {"source_file": "25_08.md"} | [
-0.0051840925589203835,
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0.006525416858494282,
0.01984909549355507,
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0.0013022167840972543,
0.07179620116949081,
0.06201395392417908,
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0.08558264374732971,
-0.009293057024478912,
-0.... |
81c19764-7cba-4a87-a418-a94c67a57d94 | Format improvements {#format-improvements}
New parquet reader implementation. It's generally faster and supports page-level filter pushdown and
PREWHERE
. Currently experimental. Use setting
input_format_parquet_use_native_reader_v3
to enable.
#82789
(
Michael Kolupaev
).
Improved performance of the ProtobufSingle input format by reusing the serializer when no parsing errors occur.
#83613
(
Eduard Karacharov
).
Data type and serialization optimizations {#data-type-and-serialization-optimizations}
Significantly improve performance of
JSON
subcolumns reading from shared data in MergeTree by implementing new serializations for
JSON
shared data in MergeTree.
#83777
(
Pavel Kruglov
).
Optimize string deserialization by simplifying the code. Closes
#38564
.
#84561
(
Alexey Milovidov
).
Pipeline and execution improvements {#pipeline-and-execution-improvements}
Minimize memory copy in port headers during pipeline construction. Original
PR
by
heymind
.
#83381
(
Raúl Marín
).
Improve the performance of pipeline building.
#83631
(
Raúl Marín
).
Optimize MergeTreeReadersChain::getSampleBlock.
#83875
(
Raúl Marín
).
Optimize the materialization of constants in cases when we do this materialization only to return a single row.
#85071
(
Alexey Milovidov
).
Memory and resource optimizations {#memory-and-resource-optimizations}
Tweak some jemalloc configs to improve performance.
#81807
(
Antonio Andelic
).
Add alignment in the Counter of ProfileEvents to reduce false sharing.
#82697
(
Jiebin Sun
).
Reduce unnecessary memcpy calls in CompressedReadBufferBase::readCompressedData.
#83986
(
Raúl Marín
).
Query planning and analysis {#query-planning-and-analysis}
Speedup of QueryTreeHash.
#82617
(
Nikolai Kochetov
).
Logging improvements {#logging-improvements}
Introduce async logging.
#82516
(
Raúl Marín
).
Function optimizations {#function-optimizations}
Optimize
largestTriangleThreeBuckets
by removing temporary data.
#84479
(
Alexey Milovidov
).
Optimized and simplified implementation of many string-handling functions. Corrected incorrect documentation for several functions. Note: The output of
byteSize
for String columns and complex types containing String columns has changed from 9 bytes per empty string to 8 bytes per empty string, which is expected behavior.
#85063
(
Alexey Milovidov
).
Keeper improvements {#keeper-improvements}
Improve Keeper with rocksdb initial loading.
#83390
(
Antonio Andelic
).
Data lake improvements {#data-lake-improvements}
Improve parallel files processing with delta-kernel-rs backend.
#85642
(
Azat Khuzhin
).
Improvements {#improvements}
Access control and security {#access-control-and-security} | {"source_file": "25_08.md"} | [
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0.06354012340307236,
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0.027750913053750992,
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-0... |
5fa64807-af0a-4fa4-8492-9e0654c0c90c | Improve parallel files processing with delta-kernel-rs backend.
#85642
(
Azat Khuzhin
).
Improvements {#improvements}
Access control and security {#access-control-and-security}
Introduced two new access types:
READ
and
WRITE
for sources and deprecates all previous access types related to sources. Before
GRANT S3 ON *.* TO user
, now:
GRANT READ, WRITE ON S3 TO user
. This also allows to separate
READ
and
WRITE
permissions for sources, e.g.:
GRANT READ ON * TO user
,
GRANT WRITE ON S3 TO user
. The feature is controlled by a setting
access_control_improvements.enable_read_write_grants
and disabled by default.
#73659
(
pufit
).
Allow parameters in
CREATE USER
queries for usernames.
#81387
(
Diskein
).
Exclude sensitive data from core dumps. Add two allocators: AWS library compatible
AwsNodumpMemoryManager
and STL compatible
JemallocNodumpSTLAllocator
. Both are wrappers of the Jemalloc allocator. They use Jemalloc's extent hooks and madvise to mark memory pages as "don't dump". Used for S3 credentials, user credentials, and some query data.
#82441
(
Miсhael Stetsyuk
).
Views, created by ephemeral users, will now store a copy of an actual user and will no longer be invalidated after the ephemeral user is deleted.
#84763
(
pufit
).
Match external auth forward_headers in case-insensitive way.
#84737
(
ingodwerust
).
Add a
parameter
column to
system.grants
to determine source type for
GRANT READ/WRITE
and the table engine for
GRANT TABLE ENGINE
.
#85643
(
MikhailBurdukov
).
Backup and restore {#backup-and-restore}
Allow backups for PostgreSQL, MySQL & DataLake databases. A backup of such a database would only save the definition and not the data inside of it.
#79982
(
Nikolay Degterinsky
).
Set all log messages for writing backup files to TRACE.
#82907
(
Hans Krutzer
).
Introduce
backup_restore_s3_retry_initial_backoff_ms
,
backup_restore_s3_retry_max_backoff_ms
,
backup_restore_s3_retry_jitter_factor
to configure the S3 retry backoff strategy used during backup and restore operations.
#84421
(
Julia Kartseva
).
Introduce a new
backup_slow_all_threads_after_retryable_s3_error
setting to reduce pressure on S3 during retry storms caused by errors such as
SlowDown
, by slowing down all threads once a single retryable error is observed.
#84854
(
Julia Kartseva
).
Data integrity and validation {#data-integrity-and-validation}
Verify the part has consistent checksum.txt file right before committing it.
#76625
(
Sema Checherinda
).
Forbid to start
RENAME COLUMN
alter mutation if it will rename some column that right now affected by incomplete data mutation.
#81823
(
Mikhail Artemenko
).
Now mutations snapshot will be built from the snapshot of visible parts. Mutation counters used in snapshot will also be recalculated from the included mutations.
#82945
(
Mikhail Artemenko
). | {"source_file": "25_08.md"} | [
-0.03497864678502083,
-0.0209509190171957,
-0.0968785434961319,
-0.030833754688501358,
0.028850432485342026,
-0.011408797465264797,
-0.030579572543501854,
-0.021382039412856102,
-0.004536034539341927,
0.061022572219371796,
0.007599396165460348,
0.02485201507806778,
0.05382469668984413,
-0.... |
0a1a079f-e0e5-4661-9630-b421336ba0ef | Now mutations snapshot will be built from the snapshot of visible parts. Mutation counters used in snapshot will also be recalculated from the included mutations.
#82945
(
Mikhail Artemenko
).
Add ability to parse part's prefix and suffix and also check coverage for non constant columns.
#83377
(
Mikhail Artemenko
).
Iceberg table engine {#iceberg-table-engine}
Support position deletes for Iceberg table engine.
#80237
(
YanghongZhong
).
Now clickhouse supports compressed
metadata.json
files for Iceberg. Fixes
#70874
.
#81451
(
alesapin
).
Fix iceberg reading by field ids for complex types.
#84821
(
scanhex12
).
Support iceberg writes to read from pyiceberg.
#84466
(
scanhex12
).
Adds snapshot version to data lake table engines.
#84659
(
Pete Hampton
).
Support writing of a version-hint file with Iceberg. This closes
#85097
.
#85130
(
scanhex12
).
Support compressed
.metadata.json
file via
iceberg_metadata_compression_method
setting. It supports all clickhouse compression methods. This closes
#84895
.
#85196
(
scanhex12
).
Optimized memory usage for Iceberg positional delete files. Instead of loading all delete file data into memory, only the current row-group from Parquet delete files is kept in RAM. This significantly reduces memory consumption when working with large positional delete files.
#85329
(
scanhex12
).
Allow asynchronously iterating objects from Iceberg table without storing objects for each data file explicitly.
#85369
(
Daniil Ivanik
).
Support Iceberg equality deletes.
#85843
(
Han Fei
).
DeltaLake table engine {#deltalake-table-engine}
Improve
DeltaLake
table engine: delta-kernel-rs has
ExpressionVisitor
API which is implemented in this PR and is applied to partition column expressions transform (it will replace an old deprecated within the delta-kernel-rs way, which was used before in our code). In the future this
ExpressionVisitor
will also allow to implement statistics based pruning and some delta-lake proprietary features. Additionally the purpose of this change is to support partition pruning in
DeltaLakeCluster
table engine (the result of a parsed expression - ActionsDAG - will be serialized and sent from the initiator along with the data path, because this kind of information, which is needed for pruning, is only available as meta information on data files listing, which is done by initiator only, but it has to be applied to data on each reading server).
#81136
(
Kseniia Sumarokova
).
Fix partition pruning with data lake cluster functions.
#82131
(
Kseniia Sumarokova
). | {"source_file": "25_08.md"} | [
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0.003202965250238776,
0.031014537438750267,
0.030032558366656303,
-0... |
ce7f8ae5-3dfd-43f3-bf54-d0ff0d59fafe | Fix partition pruning with data lake cluster functions.
#82131
(
Kseniia Sumarokova
).
Fix reading partitioned data in DeltaLakeCluster table function. In this PR cluster functions protocol version is increased, allowing to send extra info from initiator to replicas. This extra info contains delta-kernel transform expression, which is needed to parse partition columns (and some other staff in the future, like generated columns, etc).
#82132
(
Kseniia Sumarokova
).
Now database Datalake throw more convenient exception. Fixes
#81211
.
#82304
(
alesapin
).
Implement internal
delta-kernel-rs
filtering (statistics and partition pruning) in storage
DeltaLake
.
#84006
(
Kseniia Sumarokova
).
Add a setting
delta_lake_enable_expression_visitor_logging
to turn off expression visitor logs as they can be too verbose even for test log level when debugging something.
#84315
(
Kseniia Sumarokova
).
Add setting
delta_lake_snapshot_version
to allow reading specific snapshot version in table engine
DeltaLake
.
#85295
(
Kseniia Sumarokova
).
Data lake integration {#data-lake-integration}
Speedup tables listing in data catalogs by asynchronous requests.
#81084
(
alesapin
).
Support
TimestampTZ
in Glue catalog. This closes
#81654
.
#83132
(
scanhex12
).
Splits FormatParserGroup on two independent structs, the first one is responsible for shared compute and IO resources, the second one is responsible for shared filter resources (filter ActionDag, KeyCondition). This is done for more flexible shared usage of these structures by different threads.
#83997
(
Daniil Ivanik
).
Add missing
partition_columns_in_data_file
to azure configuration.
#85373
(
Arthur Passos
).
Add show_data_lake_catalogs_in_system_tables flag to manage adding data lake tables in system.tables resolves
#85384
.
#85411
(
Smita Kulkarni
).
S3 and object storage {#s3-and-object-storage}
Implement methods
moveFile
and
replaceFile
in
s3_plain_rewritable
to support it as a database disk.
#79424
(
Tuan Pham Anh
).
S3 read and write requests are throttled on the HTTP socket level (instead of whole S3 requests) to avoid issues with
max_remote_read_network_bandwidth_for_server
and
max_remote_write_network_bandwidth_for_server
throttling.
#81837
(
Sergei Trifonov
).
This PR introduces jitter to the S3 retry mechanism when the
s3_slow_all_threads_after_network_error
configuration is enabled.
#81849
(
zoomxi
).
Implement AWS S3 authentication with an explicitly provided IAM role. Implement OAuth for GCS. These features were recently only available in ClickHouse Cloud and are now open-sourced. Synchronize some interfaces such as serialization of the connection parameters for object storages.
#84011
(
Alexey Milovidov
).
Allow to use any storage policy (i.e. object storage, such as S3) for external aggregation/sorting.
#84734
(
Azat Khuzhin
). | {"source_file": "25_08.md"} | [
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-0.005663901101797819,
0.0133920693770051,
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0.04857977479696274,
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0.012125822715461254,
-0.06... |
7efb5891-36a4-4020-aba0-0be17106092b | Allow to use any storage policy (i.e. object storage, such as S3) for external aggregation/sorting.
#84734
(
Azat Khuzhin
).
Collect all removed objects to execute single object storage remove operation.
#85316
(
Mikhail Artemenko
).
S3Queue table engine {#s3queue-table-engine}
Macros like
{uuid}
can now be used in the
keeper_path
setting of the S3Queue table engine.
#82463
(
Nikolay Degterinsky
).
Add a new server setting
s3queue_disable_streaming
which disables streaming in tables with S3Queue table engine. This setting is changeable without server restart.
#82515
(
Kseniia Sumarokova
).
Add columns
commit_time
,
commit_id
to
system.s3queue_log
.
#83016
(
Kseniia Sumarokova
).
Add logs for s3queue shutdown process.
#83163
(
Kseniia Sumarokova
).
Shutdown S3(Azure/etc)Queue streaming before shutting down any tables on server shutdown.
#83530
(
Kseniia Sumarokova
).
Support changing mv insert settings on
S3Queue
table level. Added new
S3Queue
level settings:
min_insert_block_size_rows_for_materialized_views
and
min_insert_block_size_bytes_for_materialized_views
. By default profile level settings will be used and
S3Queue
level settings will override those.
#83971
(
Kseniia Sumarokova
).
S3Queue ordered mode fix: quit earlier if shutdown was called.
#84463
(
Kseniia Sumarokova
).
Kafka integration {#kafka-integration}
Count consumed messages manually to avoid depending on previous committed offset in StorageKafka2.
#81662
(
János Benjamin Antal
).
Integrate
StorageKafka2
to
system.kafka_consumers
.
#82652
(
János Benjamin Antal
).
ClickHouse Keeper improvements {#clickhouse-keeper-improvements}
Keeper improvement: move changelog files between disk in a background thread. Previously, moving changelog to a different disk would block Keeper globally until the move is finished. This lead to performance degradation if moving is a long operation (e.g. to S3 disk).
#82485
(
Antonio Andelic
).
Keeper improvement: add new config
keeper_server.cleanup_old_and_ignore_new_acl
. If enabled, all nodes will have their ACLs cleared while ACL for new requests will be ignored. If the goal is to completely remove ACL from nodes, it's important to leave the config enabled until a new snapshot is created.
#82496
(
Antonio Andelic
).
Keeper improvement: support specific permissions for world:anyone ACL.
#82755
(
Antonio Andelic
).
Add support for specifying extra Keeper ACL for paths in config. If you want to add extra ACL for a specific path you define it in the config under
zookeeper.path_acls
.
#82898
(
Antonio Andelic
).
Adds ProfileEvent when Keeper rejects a write due to soft memory limit.
#82963
(
Xander Garbett
).
Enable
create_if_not_exists
,
check_not_exists
,
remove_recursive
feature flags in Keeper by default which enable new types of requests.
#83488
(
Antonio Andelic
). | {"source_file": "25_08.md"} | [
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0.01400439441204071,
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0.028088519349694252,
0.023724859580397606,
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0.06164218485355377,
0.12915484607219696,
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0.050562694668769836,
0.06341622769832611,
-0.008667... |
1dcd2226-9042-4d17-9b28-f5228cc0ffb5 | Enable
create_if_not_exists
,
check_not_exists
,
remove_recursive
feature flags in Keeper by default which enable new types of requests.
#83488
(
Antonio Andelic
).
Add support for applying extra ACL on specific Keeper nodes using
apply_to_children
config.
#84137
(
Antonio Andelic
).
Add
get_acl
command to KeeperClient.
#84641
(
Antonio Andelic
).
Add 4LW in Keeper,
lgrq
, for toggling request logging of received requests.
#84719
(
Antonio Andelic
).
Reduce contention on storage lock in Keeper.
#84732
(
Antonio Andelic
).
The
encrypt_decrypt
tool now supports encrypted ZooKeeper connections.
#84764
(
Roman Vasin
).
Limit Keeper log entry cache size by number of entries using
keeper_server.coordination_settings.latest_logs_cache_entry_count_threshold
and
keeper_server.coordination_settings.commit_logs_cache_entry_count_threshold
.
#84877
(
Antonio Andelic
).
JSON and Dynamic types {#json-and-dynamic-types}
Add
columns_substreams.txt
file to Wide part to track all substreams stored in the part. It helps to track dynamic streams in JSON and Dynamic types and so avoid reading sample of these columns to get the list of dynamic streams (for example for columns sizes calculation). Also now all dynamic streams are reflected in
system.parts_columns
.
#81091
(
Pavel Kruglov
).
Allow
ALTER UPDATE
in JSON and Dynamic columns.
#82419
(
Pavel Kruglov
).
Users can now use
Time
and
Time64
types inside the JSON type.
#83784
(
Yarik Briukhovetskyi
).
Add a setting
json_type_escape_dots_in_keys
to escape dots in JSON keys during JSON type parsing. The setting is disabled by default.
#84207
(
Pavel Kruglov
).
Parquet and ORC formats {#parquet-and-orc-formats}
Introduce settings to set ORC compression block size, and update its default value from 64KB to 256KB to keep consistent with spark or hive.
#80602
(
李扬
).
Support writing parquet enum as byte array as the
spec
dictates. I'll write more info later.
#81090
(
Arthur Passos
).
Support writing geoparquets as output format.
#81784
(
scanhex12
).
Distributed queries and parallel replicas {#distributed-queries-and-parallel-replicas}
A new setting, enable_add_distinct_to_in_subqueries, has been introduced. When enabled, ClickHouse will automatically add DISTINCT to subqueries in IN clauses for distributed queries. This can significantly reduce the size of temporary tables transferred between shards and improve network efficiency. Note: This is a trade-off—while network transfer is reduced, additional merging (deduplication) work is required on each node. Enable this setting when network transfer is a bottleneck and the merging cost is acceptable.
#81908
(
fhw12345
).
Add support of
remote-()
table functions with parallel replicas if cluster is provided in
address_expression
argument. Also, fixes
#73295
.
#82904
(
Igor Nikonov
). | {"source_file": "25_08.md"} | [
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-0.0531858466565609,
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-0.0012838452821597457,
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0.05251525714993477,
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-0.06467557698488235,
0.036637645214796066,
0.0614... |
3caae62d-bfc6-4793-9047-1b3a233fafb6 | Add support of
remote-()
table functions with parallel replicas if cluster is provided in
address_expression
argument. Also, fixes
#73295
.
#82904
(
Igor Nikonov
).
Joins with parallel replicas now use the join logical step. In case of any issues with join queries using parallel replicas, try
SET query_plan_use_new_logical_join_step=0
and report an issue.
#83801
(
Vladimir Cherkasov
).
Settings and configuration {#settings-and-configuration}
Mark setting
allow_experimental_join_condition
as obsolete.
#80566
(
Vladimir Cherkasov
).
The total and per-user network throttlers are never reset, which ensures that
max_network_bandwidth_for_all_users
and
max_network_bandwidth_for_all_users
limits are never exceeded.
#81729
(
Sergei Trifonov
).
Introduce the
optimize_rewrite_regexp_functions
setting (enabled by default), which allows the optimizer to rewrite certain
replaceRegexpAll
,
replaceRegexpOne
, and
extract
calls into simpler and more efficient forms when specific regular expression patterns are detected. (issue
#81981
).
#81992
(
Amos Bird
).
Tune TCP servers queue (64 by default) based on listen_backlog (4096 by default).
#82045
(
Azat Khuzhin
).
Add ability to reload
max_local_read_bandwidth_for_server
and
max_local_write_bandwidth_for_server
on fly without restart server.
#82083
(
Kai Zhu
).
Introduce setting
enable_vector_similarity_index
which must be enabled to use the vector similarity index. The existing setting
allow_experimental_vector_similarity_index
is now obsolete. It still works in case someone needs it.
#83459
(
Robert Schulze
).
Add
max_joined_block_size_bytes
in addition to
max_joined_block_size_rows
to limit the memory usage of JOINs with heavy columns.
#83869
(
Nikolai Kochetov
).
Fix compatibility for cluster_function_process_archive_on_multiple_nodes.
#83968
(
Kseniia Sumarokova
).
Enable correlated subqueries support by default.
#85107
(
Dmitry Novik
).
Add
database_replicated
settings defining the default values of DatabaseReplicatedSettings. If the setting is not present in the Replicated DB create query, the value from this setting is used.
#85127
(
Tuan Pham Anh
).
Allow key value arguments in
s3
or
s3Cluster
table engine/function, e.g. for example
s3('url', CSV, structure = 'a Int32', compression_method = 'gzip')
.
#85134
(
Kseniia Sumarokova
).
Execute non-correlated
EXISTS
as a scalar subquery. This allows using a scalar subquery cache and constant-folding the result, which is helpful for indexes. For compatibility, the new setting
execute_exists_as_scalar_subquery=1
is added.
#85481
(
Nikolai Kochetov
).
Support resolution of more cases for compound identifiers. Particularly, it improves the compatibility of
ARRAY JOIN
with the old analyzer. Introduce a new setting
analyzer_compatibility_allow_compound_identifiers_in_unflatten_nested
to keep the old behaviour.
#85492
(
Nikolai Kochetov
). | {"source_file": "25_08.md"} | [
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0.05194422975182533,
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0.054345469921827316,
-... |
c6d05fac-be7f-4aee-940a-91039dd3968f | System tables and observability {#system-tables-and-observability}
Add pressure metrics to ClickHouse async metrics.
#80779
(
Xander Garbett
).
Add metrics
MarkCacheEvictedBytes
,
MarkCacheEvictedMarks
,
MarkCacheEvictedFiles
for tracking evictions from the mark cache. (issue
#60989
).
#80799
(
Shivji Kumar Jha
).
The
system.formats
table now contains extended information about formats, such as HTTP content type, the capabilities of schema inference, etc.
#81505
(
Alexey Milovidov
).
Add support for clearing all warnings from the
system.warnings
table using
TRUNCATE TABLE system.warnings
.
#82087
(
Vladimir Cherkasov
).
List the licenses of rust crates in
system.licenses
.
#82440
(
Raúl Marín
).
Estimate complex cnf/dnf, for example,
(a < 1 and a > 0) or b = 3
, by statistics.
#82663
(
Han Fei
).
In some cases, we need to have multiple dimensions to our metrics. For example, counting failed merges or mutations by error codes rather than having a single counter.
#83030
(
Miсhael Stetsyuk
).
Add process resource metrics (such as
UserTimeMicroseconds
,
SystemTimeMicroseconds
,
RealTimeMicroseconds
) to part_log profile events for
MergeParts
entries.
#83460
(
Vladimir Cherkasov
).
Cgroup-level and system-wide metrics are reported now altogether. Cgroup-level metrics have names
CGroup<Metric>
and OS-level metrics (collected from procfs) have names
OS<Metric>
.
#84317
(
Nikita Taranov
).
Add dimensional metrics to monitor the size of concurrent bounded queues, labeled by queue type and instance ID for better observability.
#84675
(
Miсhael Stetsyuk
).
The
system.columns
table now provides
column
as an alias for the existing
name
column.
#84695
(
Yunchi Pang
).
Add format string column to
system.errors
. This column is needed to group by the same error type in alerting rules.
#84776
(
Miсhael Stetsyuk
).
Make limits tunable for Async Log and add introspection.
#85105
(
Raúl Marín
).
Ignore
UNKNOWN_DATABASE
while obtaining table columns sizes for system.columns.
#85632
(
Azat Khuzhin
).
Database engines {#database-engines}
System and internal improvements {#system-and-internal-improvements}
Fix attaching databases with read-only remote disks by manually adding table UUIDs to the DatabaseCatalog.
#82670
(
Tuan Pham Anh
).
Improve DDL task handling when
distributed_ddl_output_mode='*_only_active'
by not waiting for new or recovered replicas that have replication lag exceeding
max_replication_lag_to_enqueue
. This helps avoid
DDL task is not finished on some hosts
errors when a new replica becomes active after initialization or recovery but has accumulated a large replication log. Also implemented
SYSTEM SYNC DATABASE REPLICA STRICT
query that waits for the replication log to fall below
max_replication_lag_to_enqueue
.
#83302
(
Alexander Tokmakov
). | {"source_file": "25_08.md"} | [
-0.025543279945850372,
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-0.13642707467079163,
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0.025196366012096405,
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0.01... |
b74dd5fe-6fdd-4ba7-ba61-fda79071c35f | Chang SystemLogs shutdown order to occur after ordinary tables (and before system tables, instead of before ordinary tables).
#83134
(
Kseniia Sumarokova
).
Add server setting
logs_to_keep
for replicated database settings, allowing configuration of the default
logs_to_keep
parameter for replicated databases. Lower values reduce the number of ZooKeeper nodes (especially beneficial when there are many databases), while higher values allow missing replicas to catch up after longer periods of downtime.
#84183
(
Alexey Khatskevich
).
Change the default value of the Replicated database setting
max_retries_before_automatic_recovery
to 10, enabling faster recovery in some cases.
#84369
(
Alexander Tokmakov
).
Optimize non-append Refreshable Materialized View DDL operations in Replicated databases by skipping creation and renaming of old temporary tables.
#84858
(
Tuan Pham Anh
).
Replication and synchronization {#replication-and-synchronization}
SystemAndInternalImprovements {#systemandinternalimprovements}
Improve
SYSTEM RESTART REPLICA
to retry table creation when ZooKeeper connection issues occur, preventing tables from being forgotten.
#82616
(
Nikolay Degterinsky
).
Add UUID validation in
ReplicatedMergeTree::executeMetadataAlter
to prevent incorrect table definitions when tables are exchanged between getting the StorageID and calling
IDatabase::alterTable
.
#82666
(
Nikolay Degterinsky
).
Remove experimental
send_metadata
logic related to experimental zero-copy replication. This code was never used, unsupported, and likely broken, with no tests to verify its functionality.
#82508
(
alesapin
).
Add support for macro expansion in
remote_fs_zero_copy_zookeeper_path
.
#85437
(
Mikhail Koviazin
).
Functions and expressions {#functions-and-expressions}
Function
addressToSymbol
and
system.symbols
table will use file offsets instead of virtual memory addresses.
#81896
(
Alexey Milovidov
).
Try to preserve element names when deriving supertypes for named tuples.
#81345
(
lgbo
).
Allow to mix different collations for the same column in different windows.
#82877
(
Yakov Olkhovskiy
).
Add function to write types into wkb format.
#82935
(
scanhex12
).
Add ability to parse
Time
and
Time64
as MM:SS, M:SS, SS, or S.
#83299
(
Yarik Briukhovetskyi
).
Function
reinterpret()
now supports conversion to
Array(T)
where
T
is a fixed-size data type (issue
#82621
).
#83399
(
Shankar Iyer
).
Fix
structureToProtobufSchema
and
structureToCapnProtoSchema
functions to correctly add a zero-terminating byte instead of using a newline, preventing missing newlines in output and potential buffer overflows in functions that depend on the zero byte (such as
logTrace
,
demangle
,
extractURLParameter
,
toStringCutToZero
, and
encrypt
/
decrypt
). Closes
#85062
.
#85063
(
Alexey Milovidov
). | {"source_file": "25_08.md"} | [
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0.038137465715408325,
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-0.04848632216453552,
-0.003401822177693248,
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0.03585660457611084,
0.... |
0522f7d5-118e-415a-b703-1f08fc2fdb75 | Fix the
regexp_tree
dictionary layout to support processing strings with zero bytes.
#85063
(
Alexey Milovidov
).
Fix the
formatRowNoNewline
function which was erroneously cutting the last character of output when called with
Values
format or any format without a newline at the end of rows.
#85063
(
Alexey Milovidov
).
Fix an exception-safety error in the
stem
function that could lead to memory leaks in rare scenarios.
#85063
(
Alexey Milovidov
).
Fix the
initcap
function for
FixedString
arguments to correctly recognize the start of words at the beginning of strings when the previous string in a block ended with a word character.
#85063
(
Alexey Milovidov
).
Fix a security vulnerability in the Apache
ORC
format that could lead to exposure of uninitialized memory.
#85063
(
Alexey Milovidov
).
Changed behavior of
replaceRegexpAll
and its alias
REGEXP_REPLACE
to allow empty matches at the end of strings even when the previous match processed the entire string (e.g.,
^a*|a*$
or
^|.*
), aligning with JavaScript, Perl, Python, PHP, and Ruby semantics but differing from PostgreSQL.
#85063
(
Alexey Milovidov
).
Optimize and simplify the implementation of many string-handling functions. Corrected incorrect documentation for several functions. Note: The output of
byteSize
for String columns and complex types containing String columns has changed from 9 bytes per empty string to 8 bytes per empty string, which is the expected behavior.
#85063
(
Alexey Milovidov
).
Allow zero step in functions
timeSeries*ToGrid()
This is part
#3
of https://github.com/ClickHouse/ClickHouse/pull/75036.
#85390
(
Vitaly Baranov
).
Support inner arrays for the function
nested
.
#85719
(
Nikolai Kochetov
).
MergeTree improvements {#mergetree-improvements}
Disable skipping indexes that depend on columns updated on the fly or by patch parts more granularly. Now, skipping indexes are not used only in parts affected by on-the-fly mutations or patch parts; previously, those indexes were disabled for all parts.
#84241
(
Anton Popov
).
Add MergeTree setting
search_orphaned_parts_drives
to limit scope to look for parts e.g. by disks with local metadata.
#84710
(
Ilya Golshtein
).
Add missing support of
read_in_order_use_virtual_row
for
WHERE
. It allows to skip reading more parts for queries with filters that were not fully pushed to
PREWHERE
.
#84835
(
Nikolai Kochetov
).
Fix usage of "compact" Variant discriminators serialization in MergeTree. Perviously it wasn't used in some cases when it could be used.
#84141
(
Pavel Kruglov
).
Add limit (table setting
max_uncompressed_bytes_in_patches
) for total uncompressed bytes in patch parts. It prevents significant slowdowns of
SELECT
queries after lightweight updates and prevents possible misuse of lightweight updates.
#85641
(
Anton Popov
).
Cache and memory management {#cache-and-memory-management} | {"source_file": "25_08.md"} | [
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-0.03262930363416672,
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0.046181946992874146,
-0.0350... |
b41a5922-cf5c-4667-8936-1bf84b941b54 | Cache and memory management {#cache-and-memory-management}
Fix logical error in filesystem cache: "Having zero bytes but range is not finished".
#81868
(
Kseniia Sumarokova
).
Add rendezvous hashing to improve cache locality.
#82511
(
Anton Ivashkin
).
Refactor dynamic resize feature of filesystem cache. Added more logs for introspection.
#82556
(
Kseniia Sumarokova
).
Reduce query memory tracking overhead for executable user-defined functions.
#83929
(
Eduard Karacharov
).
All the allocations done by external libraries are now visible to ClickHouse's memory tracker and accounted properly. This may result in "increased" reported memory usage for certain queries or failures with
MEMORY_LIMIT_EXCEEDED
.
#84082
(
Nikita Mikhaylov
).
Allocate the minimum amount of memory needed for encrypted_buffer for encrypted named collections.
#84432
(
Pablo Marcos
).
Vector similarity index {#vector-similarity-index}
Prevent user from using
nan
and
inf
with
NumericIndexedVector
. Fixes
#82239
and a little more.
#82681
(
Raufs Dunamalijevs
).
The vector similarity index now supports binary quantization. Binary quantization significantly reduces the memory consumption and speeds up the process of building a vector index (due to faster distance calculation). Also, the existing setting
vector_search_postfilter_multiplier
was made obsolete and replaced by a more general setting :
vector_search_index_fetch_multiplier
.
#85024
(
Shankar Iyer
).
Approximate vector search with vector similarity indexes is now GA.
#85888
(
Robert Schulze
).
Error handling and messages {#error-handling-and-messages}
Header Connection is sent at the end of headers. When we know is the connection should be preserved.
#81951
(
Sema Checherinda
).
In previous versions, multiplication of the aggregate function state with IPv4 produced a logical error instead of a proper error code. Closes
#82817
.
#82818
(
Alexey Milovidov
).
Better error handling in
AsynchronousMetrics
. If the
/sys/block
directory exists but is not accessible, the server will start without monitoring the block devices. Closes
#79229
.
#83115
(
Alexey Milovidov
).
There was an incorrect dependency check for the
INSERT
with materialized views that have malformed selects and the user might have received an obscure
std::exception
instead of a meaningful error with a clear explanation. This is now fixed. This fixes:
#82889
.
#83190
(
Nikita Mikhaylov
).
Do not output very long descriptions of expression actions in exception messages. Closes
#83164
.
#83350
(
Alexey Milovidov
).
When the storage is shutting down,
getStatus
throws an
ErrorCodes::ABORTED
exception. Previously, this would fail the select query. Now we catch the
ErrorCodes::ABORTED
exceptions and intentionally ignore them instead.
#83435
(
Miсhael Stetsyuk
). | {"source_file": "25_08.md"} | [
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0.0... |
8334e162-1ad7-4f9f-aefe-38b95f21f35e | Make exception messages for certain situations for loading and adding projections easier to read.
#83728
(
Robert Schulze
).
Check if connection is cancelled before checking for EOF to prevent reading from closed connection. Fixes
#83893
.
#84227
(
Raufs Dunamalijevs
).
Improved server shutdown handling for client connections by simplifying internal checks.
#84312
(
Raufs Dunamalijevs
).
Low-level errors during UDF execution now fail with error code
UDF_EXECUTION_FAILED
, whereas previously different error codes could be returned.
#84547
(
Xu Jia
).
SQL formatting improvements {#sql-formatting-improvements}
Fix inconsistent formatting of
CREATE DICTIONARY
. Closes
#82105
.
#82829
(
Alexey Milovidov
).
Fix inconsistent formatting of
TTL
when it contains a
materialize
function. Closes
#82828
.
#82831
(
Alexey Milovidov
).
Fix inconsistent formatting of
EXPLAIN AST
in a subquery when it contains output options such as INTO OUTFILE. Closes
#82826
.
#82840
(
Alexey Milovidov
).
Fix inconsistent formatting of parenthesized expressions with aliases in the context when no aliases are allowed. Closes
#82836
. Closes
#82837
.
#82867
(
Alexey Milovidov
).
Fix formatting of CREATE USER with query parameters (i.e.
CREATE USER {username:Identifier} IDENTIFIED WITH no_password
).
#84376
(
Azat Khuzhin
).
Fix parsing of a trailing comma in columns of the CREATE DICTIONARY query after a column with parameters, for example, Decimal(8). Closes
#85586
.
#85653
(
Nikolay Degterinsky
).
External integrations {#external-integrations}
Unify parameter names in ODBC and JDBC when using named collections.
#83410
(
Andrey Zvonov
).
MongoDB: Implicit parsing of strings to numeric types. Previously, if a string value was received from a MongoDB source for a numeric column in a ClickHouse table, an exception was thrown. Now, the engine attempts to parse the numeric value from the string automatically. Closes
#81167
.
#84069
(
Kirill Nikiforov
).
Allow
simdjson
on unsupported architectures (previously leads to
CANNOT_ALLOCATE_MEMORY
errors).
#84966
(
Azat Khuzhin
).
Miscellaneous improvements {#miscellaneous-improvements}
Add Ytsaurus table engine and table function.
#77606
(
MikhailBurdukov
).
Improve HashJoin::needUsedFlagsForPerRightTableRow, returns false for cross join.
#82379
(
lgbo
).
Allow write/read map columns as array of tuples.
#82408
(
MikhailBurdukov
).
This PR was reverted.
#82884
(
Mithun p
).
Async logs: Limit the max number of entries that are hold in the queue.
#83214
(
Raúl Marín
).
Enable Date/Date32 as integers in JSON input formats.
#83597
(
MikhailBurdukov
).
Improved support for bloom filter indexes (regular, ngram, and token) to be utilized when the first argument is a constant array (the set) and the second is the indexed column (the subset), enabling more efficient query execution.
#84700
(
Doron David
). | {"source_file": "25_08.md"} | [
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1cc8ba14-a75e-4e1b-a1b4-2481b19c4f43 | Allow set values type casting when pushing down
IN
/
GLOBAL IN
filters over KeyValue storage primary keys (e.g., EmbeddedRocksDB, KeeperMap).
#84515
(
Eduard Karacharov
).
Eliminated full scans for the cases when index analysis results in empty ranges for parallel replicas reading.
#84971
(
Eduard Karacharov
).
Fix a list of problems that can occur when trying to run integration tests on a local host.
#82135
(
Oleg Doronin
).
Enable trace_log.symbolize for old deployments by default.
#85456
(
Azat Khuzhin
).
Bug fixes (user-visible misbehavior in an official stable release) {#bug-fixes}
Performance optimizations {#performance-optimizations}
Fix performance degradation in SummingMergeTree that was intorduced in 25.5 in https://github.com/ClickHouse/ClickHouse/pull/79051.
#82130
(
Pavel Kruglov
).
Fix performance degradation with the enabled analyzer when secondary queries always read all columns from the VIEWs. Fixes
#81718
.
#83036
(
Dmitry Novik
).
Do not check for cyclic dependencies on create table with no dependencies. It fixes performance degradation of the use cases with creation of thousands of tables that was introduced in https://github.com/ClickHouse/ClickHouse/pull/65405.
#83077
(
Pavel Kruglov
).
Make
DISTINCT
window aggregates run in linear time and fix a bug in
sumDistinct
. Closes
#79792
. Closes
#52253
.
#79859
(
Nihal Z. Miaji
).
Query execution fixes {#query-execution-fixes}
For queries with combination of
ORDER BY ... LIMIT BY ... LIMIT N
, when ORDER BY is executed as a PartialSorting, the counter
rows_before_limit_at_least
now reflects the number of rows consumed by LIMIT clause instead of number of rows consumed by sorting transform.
#78999
(
Eduard Karacharov
).
Fix logical error with
<=>
operator and Join storage, now query returns proper error code.
#80165
(
Vladimir Cherkasov
).
Fix a crash in the
loop
function when used with the
remote
function family. Ensure the LIMIT clause is respected in
loop(remote(...))
.
#80299
(
Julia Kartseva
).
Fix incorrect behavior of
to_utc_timestamp
and
from_utc_timestamp
functions when handling dates before Unix epoch (1970-01-01) and after maximum date (2106-02-07 06:28:15). Now these functions properly clamp values to epoch start and maximum date respectively.
#80498
(
Surya Kant Ranjan
).
Fix
IN
execution with
transform_null_in=1
with null in the left argument and non-nullable subquery result.
#81584
(
Pavel Kruglov
).
Fix the issue where required columns are not read during scalar correlated subquery processing. Fixes
#81716
.
#81805
(
Dmitry Novik
).
Fix filter analysis when only a constant alias column is used in the query. Fixes
#79448
.
#82037
(
Dmitry Novik
).
Fix the
Not found column
error for queries with
arrayJoin
under
WHERE
condition and
IndexSet
.
#82113
(
Nikolai Kochetov
). | {"source_file": "25_08.md"} | [
0.012918217107653618,
0.032412800937891006,
-0.05465732514858246,
0.0577193982899189,
-0.04488556459546089,
-0.028852486982941628,
0.002419290831312537,
-0.01503105740994215,
-0.07601077109575272,
-0.005522661376744509,
-0.026093024760484695,
-0.04179681837558746,
0.02960951440036297,
0.00... |
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