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Region availability
Lakebase Autoscaling is the latest version of Lakebase, with autoscaling compute, scale-to-zero, branching, and instant restore. For supported regions, see Region availability. If you are a Lakebase Provisioned user, see Lakebase Provisioned.
Lakebase Autoscaling is serverless Postgres with automatic scaling, instant branching, and native integration with Unity Catalog and the lakehouse. Connect with any Postgres client or driver. Compute scales to match your workload and suspends when idle. Branches create isolated copies of your database using copy-on-write storage.
Two ways to start. Pick the one that fits how you'll use the database.
Start with Postgres
Provision a Lakebase database directly, then connect your code or move data between Postgres and the lakehouse. Best for engineers comfortable with standard Postgres clients (psql, drivers, frameworks) and for evaluating autoscaling and branching.
| Quickstart | When to use |
|---|---|
| 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. |
Key features
Explore features that optimize performance, reduce costs, and enable flexible development workflows.
| Feature | Description |
|---|---|
| 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. |
Connect and query
Use various tools and interfaces to connect to and query your database.
| Task | Description |
|---|---|
| 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. |
Databricks integrations
Connect Lakebase with your existing Databricks data and workflows.
| Integration | Description |
|---|---|
| Register in Unity Catalog | Register your Lakebase database in Unity Catalog for unified governance. |
| Serve data with synced tables | Serve lakehouse data through your Lakebase database for low-latency applications. |
| Lakehouse Sync | Continuously sync Lakebase tables to Unity Catalog Delta tables for analytics and history. (Beta) |
| Databricks Apps | Build and deploy interactive applications with Lakebase as the managed Postgres backend. |
| Agent state and memory | Store durable short-term and long-term agent memory in Lakebase for AI agents built with LangGraph or the OpenAI Agents SDK. |
| Feature Store and Model Serving | Use Lakebase as a low-latency online feature store backend for ML models served with Model Serving. |
Start with Databricks Apps
Deploy a Databricks App with a managed Lakebase Postgres connection. Best for new apps, dashboards, and internal tools where credentials, identity, and scaling are handled for you.
| Path | When to use |
|---|---|
| Build applications | Choose a templated Databricks App, a custom Databricks App, or an external app integration. Compare approaches before you start building. |
Learn more
| Resource | Description |
|---|---|
| Use cases | Lakebase patterns: serve lakehouse data, replicate to the lakehouse, application backend, AI agents and ML. |
| What is Lakebase? | Architecture, branching model, and product overview. |