Set up query federation for non-Unity-Catalog workspaces

Experimental

The configurations described in this article are Experimental. Experimental features are provided as-is and are not supported by Databricks through customer technical support. To get full query federation support, you should instead use Lakehouse Federation, which enables your Databricks users to take advantage of Unity Catalog syntax and data governance tools.

The term query federation describes a collection of features that enable users and systems to run queries against multiple external data sources without needing to migrate all data to a unified system.

To get full query federation support, you should use Lakehouse Federation, which enables your Databricks users to take advantage of Unity Catalog syntax and data governance tools. However, if you do not have access to a Unity-Catalog-enabled workspace, you have many options for running queries against data in external data sources, including:

• Databricks-provided JDBC and ODBC drivers that are compatible with many BI tools.

• Databricks partner integrations, with a number of available BI and visualization tools that support querying data in the lakehouse.

• Delta Sharing, which provides an open source protocol and extended Databricks support for sharing Delta Lake tables with users connecting from numerous third-party clients and other Databricks workspaces.

• Open source storage integrations for data that uses the Delta protocol.

• The experimental connection configurations described in the following articles:

  • PostgreSQL
  • MySQL
  • Snowflake
  • Redshift
  • Synapse
  • SQL Server

  Drivers for the database solutions described in the articles listed above are included on all Databricks Runtime clusters, as well as Serverless and Pro SQL warehouses.