databricks-lakebase-autoscale
Lakebase Autoscaling
Lakebase Autoscaling is Databricks' next-generation managed PostgreSQL service for OLTP workloads: autoscaling compute, database branching, scale-to-zero, instant restore, and Delta-to-Postgres synced tables.
Use this skill when creating/managing Lakebase Autoscaling projects, branches, endpoints/computes, credentials, reverse ETL synced tables, or app connections.
Core framing
There is no separate Python “Lakebase SDK.” Use
databricks-sdkfor management and for minting short-lived database credentials withWorkspaceClient().postgres.generate_database_credential(...); use standard Postgres drivers (psycopg, SQLAlchemy, JDBC,pgx, etc.) for SQL.
| Language | Credential / management SDK | DB driver / wrapper |
|---|---|---|
| Python | databricks-sdk WorkspaceClient().postgres |
psycopg[binary,pool] canonical; SQLAlchemy supported |
| Node/TS | @databricks/lakebase convenience wrapper, Autoscaling only |
Wrapper manages pg pool |
| Java/Go | Databricks SDK for Java/Go | Standard JDBC / pgx |
Lead connection pattern
For production Python apps, start with:
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