How does Lakebase integrate with existing Postgres applications?

Summary

• Lakebase is fully PostgreSQL-compatible, so existing applications work unchanged: point your connection string at Lakebase and you're done, no rewrite needed.
• Standard Postgres drivers, ORMs, and tools (psycopg3, SQLAlchemy, pgvector, PostGIS) all work out of the box without modification.
• Lakebase Migrator automates imports from pg_dump files; a Migration Assistant (targeting early 2027 GA) will support low-downtime migrations from external Postgres systems like RDS.
• Native integration with the Databricks lakehouse eliminates custom ETL: synced tables serve analytical data with OLTP latency, and Change Data Feed streams changes as Delta tables.

How does Lakebase integrate with existing Postgres applications?

Lakebase integrates with existing Postgres applications without friction: your application code, queries, and libraries work without modification because Lakebase is PostgreSQL-compatible. Migrate by changing a single connection string and repointing your application to Lakebase. No rewrite, no refactoring, no months of planning.

PostgreSQL compatibility: what works out of the box

Lakebase is a fully managed PostgreSQL database supporting Postgres versions 16, 17, and 18. This means:

• All standard Postgres drivers work: psycopg3 for Python, JDBC for Java, Ruby pg, Node postgres, and language-native bindings all connect as they would to a traditional Postgres server.
• Popular ORMs are fully supported: SQLAlchemy, Sequelize, Prisma, Hibernate, and others need no code changes.
• Postgres extensions are available: pgvector for embeddings, PostGIS for geospatial data, UUID generation, and other standard extensions run as normal.
• Your SQL queries, indexes, transactions, and stored procedures are unchanged. Lakebase understands standard Postgres syntax and behavior.
• Connection pooling and application patterns work identically: connection strings, SSL, username/password authentication, and OAuth all follow standard Postgres conventions.

Migration from your existing Postgres database

Migration scenario	Lakebase approach	Timeline
Proof of concept	Lakebase Migrator with pg_dump import (supported now)	Immediate
Development/test databases	Instant branching: zero-copy clones in seconds for risk-free testing and staging	Immediate
Production RDS/cloud Postgres	Migration Assistant for managed, low-downtime migration (targets beta Oct 2026, GA Jan 2027)	Q4 2026 / Q1 2027
Non-Postgres databases	Enhanced tooling (Lakebridge) planned for other database sources in future roadmap	Planned

For existing databases, the Lakebase Migrator supports import from pg_dump files today. You export your schema and data in standard Postgres format, import to Lakebase, and your application connects to the new database. The Lakebase Migration Assistant (coming soon) will handle direct connections to RDS and other cloud Postgres systems, automating schema translation, large table copies, and cutover orchestration to minimize downtime.

Connection methods: flexibility for different patterns

Native PostgreSQL drivers. Use any Postgres library (psycopg, JDBC, Node postgres, etc.) for full DDL and DML support. Your application connects exactly as it would to a cloud Postgres instance.
Lightweight Data API. For serverless or low-footprint use cases, Lakebase offers a REST API that doesn't require persistent connections. Useful for HTTP-triggered workloads (Lambda, Cloud Functions) and stateless microservices.
Authentication with your Databricks workspace identity. Connect using the same OAuth token or service principal as your Databricks account. No separate identity system to manage.

Lakehouse integration: from ETL to managed sync

Once your application runs on Lakebase, you gain native integration with the Databricks lakehouse without writing ETL pipelines.
Synced tables (GA). Register a table from Unity Catalog (your analytical data) in Lakebase as a read-only synced table. Applications then read fresh data with OLTP latency instead of running expensive queries to the lakehouse. No manual sync code, no staleness gap.
Change Data Feed (Public Preview on Azure). Automatically stream row-level changes from Lakebase as Delta tables. Downstream pipelines consume changes on their schedule instead of polling or building CDC infrastructure.
Lakehouse//RT (Beta on Azure). Run transactionally consistent analytical queries on live Lakebase data without blocking application workloads. A dashboard can scan your entire transaction table while payments process.
Unity Catalog governance. Register Lakebase tables in the catalog. Access control, data masking, and audit logs apply automatically. Lineage flows between your application data and analytical workloads.

Developer experience: modern database primitives

Instant branching. Create zero-copy database clones in seconds for testing, staging, or schema experiments. Branch off production, test a migration or schema change, and discard without affecting your running application.
Point-in-time recovery (PITR). Restore to any moment in the past instantly. No backups to restore, no downtime. This eliminates the risk of accidental data loss during testing.
Autoscaling and scale-to-zero. Compute scales automatically with workload. When idle, Lakebase scales to zero and you pay nothing for compute. Ideal for dev/test and variable production workloads.

What remains unchanged in your application

Your application code, queries, connection pooling, and error handling remain the same. No retraining, no refactoring, no new libraries to learn. This is the core promise of Postgres compatibility: Lakebase runs the database workload while you keep your application investment.

FAQs

Can I use Lakebase as a drop-in replacement for my RDS Postgres?

Yes for applications; it's a managed Postgres database with the same SQL compatibility. The main difference is that Lakebase integrates with the Databricks lakehouse, provides instant branching and scale-to-zero, and has lower compute costs for bursty workloads.

Will my ORM (SQLAlchemy, Prisma, etc.) work on Lakebase?

Yes. Lakebase speaks standard Postgres SQL and protocol. Any Postgres-compatible ORM works unchanged.

How do I migrate without downtime?

The Migration Assistant (coming early 2027) will handle managed, low-downtime cutover. For now, Lakebase Migrator supports pg_dump imports; your team orchestrates the cutover window.

Can I use pgvector for embeddings?

Yes. Lakebase supports pgvector and other standard Postgres extensions. Build AI-native applications with vector similarity search directly in your transactional database.