About ClickHouse
Managed Databases for ClickHouse are currently in beta.
Cloud Databases for ClickHouse is a managed analytical DBMS in the cloud based on ClickHouse. The DBMS is suitable for real-time analytical data processing (OLAP, Online Analytical Processing). ClickHouse allows you to execute SQL queries with complex calculations on large datasets.
Learn more about this DBMS in the official ClickHouse documentation.
Use cases
- real-time business intelligence and dashboard creation;
- web and product analytics;
- log and event storage and analysis;
- infrastructure and service monitoring;
- time series analysis.
Versions
ClickHouse version 26.3.12.3 is supported.
How it works
To get started, create a cluster. You can create a cluster by:
- in the control panel;
- via Managed Databases API.
A ClickHouse cluster consists of node groups. When creating a cluster, you choose a configuration for each node group—the number of vCPUs, RAM, and disk size. All nodes in a group will have the same configuration.
Configurations are divided into lines. Depending on the line, configurations can be:
- fixed — configurations with different technical specifications that have a fixed resource ratio;
- custom — configurations in which you can specify the resource ratio.
Cloud Databases for ClickHouse support sharding. You can also create a fault-tolerant cluster with data replication.
A ClickHouse cluster can only be connected to a private subnet. To connect to the cluster from the internet, use a public IP address. You can configure network access to the cluster to filter incoming and outgoing traffic.
DBMS settings are selected by default when creating a cluster and depend on the cluster configuration. You can change them if necessary.
How to work with Managed Databases for ClickHouse
You can work with a ClickHouse cluster through the control panel or the Managed Databases API.
To start working with a cluster, connect to it and create a database.
After creating a cluster, you can:
- monitor its status using monitoring in the control panel;
- collect and analyze cluster logs;
- scale the cluster;
- improve cluster fault tolerance;
- manage shard groups.