Agent memory
BetaManaged, Lakebase-backed state for agents built on any framework, part of Agent Bricks. Agent sessions keep the conversation history of one interaction, agent memory keeps facts, preferences and workflows that an agent recalls in later conversations through combined full-text and semantic search, and memory pipelines use an LLM to distill sessions into memories on demand or about every 24 hours. Stores are workspace-scoped with store-level access control, and Databricks says the design follows its MemCurrent memory research, which also powers memory in Genie. The first version, launched in Beta on 2026-06-23 as Unity Catalog memory stores, is now legacy and deprecated in the docs. Lakebase-backed memory and sessions joined on 2026-09-16 and memory pipelines on 2026-10-12. This row was previously listed as Managed agent memory.
Status history
- Beta
Sources (4)
- 2026-10-20Databricks Blog Beta
- 2026-10-12Release notes Beta
- 2026-09-16Release notes Beta
- 2026-06-23Release notes Beta
Recent coverage
- 2026-10-20Introducing Agent Memory on Databricks news
- 2026-10-20MemCurrent: Designing Persistent Memory for Production Agents news
- 2026-10-19Building Production-Ready AI Agents on Databricks | Agent Bricks Demo video
- 2026-10-19Introducing Agent Memory on Databricks video
- 2026-10-12Agent Bricks: The Agent Developer Platform | Overview video
- 2026-10-01Demo: Building a Governed AI Agent with Unity AI Gateway video
Status and dates are extracted from public sources only. We don't see the private AE-shared roadmap. If something looks wrong, tell us.