Integration with the Lakekeeper Catalog works with Iceberg tables only.
This integration supports both AWS S3 and other cloud storage providers.
- Rust native implementation for high performance and reliability
- REST API compliance with the Iceberg REST catalog specification
- Cloud storage integration with S3-compatible storage
As this feature is experimental, you will need to enable it using:
SET allow_experimental_database_iceberg = 1;Local Development Setup
For local development and testing, you can use a containerized Lakekeeper setup. This approach is ideal for learning, prototyping, and development environments.Prerequisites
- Docker and Docker Compose: Ensure Docker is installed and running
- Sample Setup: You can use the Lakekeeper docker-compose setup
Setting up Local Lakekeeper Catalog
You can use the official Lakekeeper docker-compose setup which provides a complete environment with Lakekeeper, PostgreSQL metadata backend, and MinIO for object storage. Step 1: Create a new folder in which to run the example, then create a filedocker-compose.yml with the following configuration:
The Lakekeeper setup requires that sample data be loaded into the Iceberg tables first. Make sure the environment has created and populated the tables before attempting to query them through ClickHouse. The availability of tables depends on the specific docker-compose setup and sample data loading scripts.
Connecting to Local Lakekeeper Catalog
Connect to your ClickHouse container:Querying Lakekeeper catalog tables using ClickHouse
Now that the connection is in place, you can start querying via the Lakekeeper catalog. For example:If you don’t see any tables, this usually means:
- The environment hasn’t created the sample tables yet
- The Lakekeeper catalog service isn’t fully initialized
- The sample data loading process hasn’t completed
Backticks requiredBackticks are required because ClickHouse doesn’t support more than one namespace.
Loading data from your Data Lake into ClickHouse
If you need to load data from the Lakekeeper catalog into ClickHouse, start by creating a local ClickHouse table:INSERT INTO SELECT: