Metadata and access control
Partner integrations should use serverless SQL warehouses for all metadata operations—reading catalogs, schemas, tables, and access policies—to ensure consistent governance and optimal performance. Review Unity Catalog privileges and securable objects, apply least-privilege access, and filter out system assets for a cleaner user experience.
Reading metadata
General metadata lookup
Use Databricks SQL driver metadata APIs, GET calls on SDKs, or SHOW commands to retrieve high-level metadata such as catalogs, schemas, tables, and other assets.
Detailed metadata for specific objects
For more detailed metadata, use SHOW and DESCRIBE EXTENDED SQL commands.
Documentation: SHOW statements | DESCRIBE statements | Information Schema
Metadata accessed through your integration must comply with the Databricks Acceptable Use Policy (AUP).
Writing metadata
- The recommended starting point for creating and modifying metadata (e.g., tables, views, catalogs, tags) is via SQL DDL statements.
- To include external assets in data lineage, use the bring-your-own-lineage API.
Documentation: SQL DDL statements | External Lineage (BYOL)
Managing access control
Databricks provides multiple layers of access control. Use SQL to write policies to Unity Catalog and let Unity Catalog handle enforcement. To manage access at scale without granting permissions on individual objects, use ABAC with governed tags. For advanced scenarios, use the Databricks REST API.
Documentation: Access control layers | ABAC | Data access control | REST API
What's next
- Learn about data ingestion patterns
- Explore data transformation capabilities
- Review the integration requirements for Unity Catalog guidance