Lakebase Postgres

Lakebase is a fully managed Postgres database integrated into the Databricks platform. Build real-time transactional applications alongside your lakehouse data, with automatic scaling, instant branching, and native Unity Catalog integration.

• Build low-latency apps: Connect Databricks Apps or any application to Lakebase for transactional workloads.
• Serve lakehouse data: Sync Unity Catalog tables into Lakebase so applications can query them at low latency.
• Store Postgres changes: Store Postgres changes as Delta tables for downstream pipelines and audit.
• AI and ML: Use Lakebase as an online feature store for ML models, or as a state store for AI agents.

If you have existing Lakebase Provisioned instances, they are being upgraded to Lakebase Autoscaling. See Upgrade to Lakebase Autoscaling.

Get started

• • Get a Postgres database
  • Create a project, branch, and database. Connect with psql or any Postgres driver.
• • Serve lakehouse data
  • Sync Unity Catalog tables into Postgres for low-latency app reads.
• • Store Postgres changes in the lakehouse
  • (Public Preview) Store Postgres changes as Delta with full change history.
• • Build applications
  • Build apps backed by Lakebase using Databricks Apps, external integrations, or the Data API.

Key features

Explore features that optimize performance, reduce costs, and enable flexible development workflows.

• • Autoscaling
  • Automatically adjust compute resources based on workload demand.
• • Scale to zero
  • Automatically suspend inactive computes to minimize costs.
• • Branches
  • Create isolated branches for development and testing.
• • Read replicas
  • Create read-only replicas to scale read operations.
• • Instant restore
  • Create a new branch from any point in time within your history window.
• • High availability
  • Configure automatic failover to keep your database available during compute failures.

Connect and query

Use various tools and interfaces to connect to and query your database.

• • Connect to your database
  • Learn different ways to connect to your Lakebase database.
• • Query with SQL Editor
  • Use the built-in SQL Editor to query and manage your database.
• • Tables editor
  • Use the visual interface to view, edit, and manage data and schemas.
• • Postgres clients
  • Connect using standard Postgres clients and tools.
• • Querying data at a point in time
  • Query data using point-in-time branches.

Learn more

• • Use cases
  • Lakebase patterns: serve lakehouse data, replicate to the lakehouse, application backend, AI agents and ML.
• • Region availability
  • Supported AWS and Azure regions for Lakebase Postgres.