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การเข้าถึงหน้านี้ต้องได้รับการอนุญาต คุณสามารถลอง ลงชื่อเข้าใช้หรือเปลี่ยนไดเรกทอรีได้
การเข้าถึงหน้านี้ต้องได้รับการอนุญาต คุณสามารถลองเปลี่ยนไดเรกทอรีได้
Connect Lakebase to the rest of Azure Databricks: register databases in Unity Catalog for governance, serve lakehouse data through Postgres for low-latency reads, feed Postgres changes back to the lakehouse, and use Lakebase as a backend for AI agents, feature serving, and search. For the architecture behind these integrations, see LTAP architecture.
| Integration | Description |
|---|---|
| Register database in Unity Catalog | Register your Lakebase database in Unity Catalog for unified governance and cross-source queries. |
| Serve data with synced tables | Sync Unity Catalog table data into Lakebase to serve it to applications at low latency. |
| Lakebase Change Data Feed | Store row-level changes from Lakebase Postgres tables as Unity Catalog Delta tables for downstream pipelines, audit, and external consumers. |
| Agent state and memory | Persist agent state and memory in Lakebase so AI agents built with LangGraph or the OpenAI Agents SDK retain context across sessions. |
| Feature Store and Model Serving | Serve ML features at low latency from Lakebase for models deployed with Databricks Model Serving. |
| Lakebase Search | Add hybrid vector and keyword search to your project using the lakebase_vector and lakebase_text extensions. |