Overview
- Databricks announced at its Data + AI Summit on Tuesday that it is shipping LTAP (Lake Transactional/Analytical Processing) to unify transactional and analytical workloads on the lakehouse so agents can read and write live data without persistent ETL or replicas.
- CustomerLake, an agentic customer data platform built inside the lakehouse, is available on Azure Databricks and uses Profile Agents and Campaign Agents to assemble Customer 360 profiles and automate personalized campaigns.
- The company expanded Lakebase with enterprise features such as Git-style branching for quick full-fidelity database forks, real-time mirroring from transactional Postgres into the lake, and Lakehouse//RT for sub-second analytics on lake data.
- Unity Catalog AI Gateway and new contextual service policies extend governance to models, agents, MCP services and external tools with unified spend controls, auditing, and fine-grained runtime rules for agent actions.
- Databricks broadened Agent Bricks and Genie with managed agent memory, document intelligence, multi-model support and Microsoft integrations like OneLake catalog federation (GA) and an Excel add-in preview to bring governed lake data into business workflows.