databricks-lakebase

To manage a Databricks Lakebase Postgres project, you can create, update, and delete Autoscaling projects using the Databricks API for project operations. This Skill automates project creation, branch management, and endpoint configuration.

Setting up Databricks Lakebase Postgres requires Databricks CLI version 0.294.0 or higher and appropriate workspace permissions. You also need to ensure your environment supports AWS or Azure for cloud infrastructure.

Yes, Databricks Lakebase supports syncing Unity Catalog Delta tables directly into Postgres. This feature allows you to maintain consistency between your lakehouse and operational PostgreSQL databases.

Branching in Databricks Lakebase Postgres uses copy-on-write branches with TTL, point-in-time recovery, and reset capabilities. This allows for safe data experimentation and rapid rollback within your project environments.

Yes, Databricks Lakebase provides high availability with one primary and up to three secondary compute nodes, featuring automatic failover. It also supports autoscaling from 0.5 to 32 compute units, including scale-to-zero.

The best way to connect an external application to a Lakebase database is through PostgreSQL connectivity with OAuth token refresh, connection pooling, and SSL. Alternatively, you can use the PostgREST-compatible HTTP Data API for CRUD operations.