Databricks is highlighting a growing set of partner-built accelerators for Lakebase that help organizations modernize operational data systems, support stateful AI applications, and deliver real-time business workflows on a governed Databricks foundation.
Whatโs new
- Migration and modernization accelerators: Several partners are using Lakebase to help teams move off legacy databases and ETL platforms with more structured migration workflows, schema and code conversion, validation, and safer cut-over rehearsal using Lakebase branching.
- Stateful memory for AI agents: A major pattern across the partner ecosystem is using Lakebase as a low-latency operational memory layer so agents can persist session context, maintain workflow state, coordinate multi-agent tasks, and support real-time writes.
- Operational and real-time application patterns: Partners are also building apps where Lakebase serves as the transactional backbone for low-latency reads and writes, app state, operational metadata, serving layers, and interactive business workflows inside Databricks.
- Ready-to-deploy functional solutions: The source highlights packaged solutions across finance, marketing, sales, supply chain, HR, customer service, and operations, showing how Lakebase is being applied to planning, procurement, personalization, proposal generation, workforce intelligence, and project operations.
- Built on Lakebase plus the wider Databricks platform: Across these partner offerings, Lakebase is commonly combined with Unity Catalog, Databricks Apps, Genie, Agent Bricks, Delta Lake, and Lakehouse services to keep transactional and analytical workflows closer together on one platform.
Databricks Lakebase is a fully managed, serverless Postgres database built into the platform, with native integrations like Synced Tables and Lakebase CDF helping move data between Lakebase and the lakehouse without separate pipelines.
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