DataLakeCatalog
The DataLakeCatalog database engine enables you to connect ClickHouse to external
data catalogs and query open table format data without the need for data duplication.
This transforms ClickHouse into a powerful query engine that works seamlessly with
your existing data lake infrastructure.
Supported Catalogs
The DataLakeCatalog engine supports the following data catalogs:
- AWS Glue Catalog - For Iceberg tables in AWS environments
- Databricks Unity Catalog - For Delta Lake and Iceberg tables
- Hive Metastore - Traditional Hadoop ecosystem catalog
- REST Catalogs - Any catalog supporting the Iceberg REST specification
Creating a Database
You will need to enable the relevant settings below to use the DataLakeCatalog engine:
Databases with the DataLakeCatalog engine can be created using the following syntax:
The following settings are supported:
| Setting | Description | 
|---|---|
| catalog_type | Type of catalog: glue,unity(Delta),rest(Iceberg),hive | 
| warehouse | The warehouse/database name to use in the catalog. | 
| catalog_credential | Authentication credential for the catalog (e.g., API key or token) | 
| auth_header | Custom HTTP header for authentication with the catalog service | 
| auth_scope | OAuth2 scope for authentication (if using OAuth) | 
| storage_endpoint | Endpoint URL for the underlying storage | 
| oauth_server_uri | URI of the OAuth2 authorization server for authentication | 
| vended_credentials | Boolean indicating whether to use vended credentials (AWS-specific) | 
| aws_access_key_id | AWS access key ID for S3/Glue access (if not using vended credentials) | 
| aws_secret_access_key | AWS secret access key for S3/Glue access (if not using vended credentials) | 
| region | AWS region for the service (e.g., us-east-1) | 
Examples
See below pages for examples of using the DataLakeCatalog engine:
