Databricks unveils Lakehouse//RT and LTAP to collapse OLTP/OLAP for agents

At the Data + AI Summit, Databricks announced two products targeting the latency that AI agents impose on operational data pipelines. Lakehouse//RT delivers millisecond query latency directly on governed Delta and Iceberg tables, eliminating the dedicated real-time serving tier alongside lakehouses. LTAP stores Postgres-native transactional data in Delta and Iceberg format from the point of write, removing ETL between operational and analytical systems. Cofounder Reynold Xin called a simpler stack "the holy grail for agents," arguing reasoning agents acting on live data can't tolerate ETL pipelines. Where prior HTAP attempts tried to converge engines, Databricks is betting that storage-layer unification on open table formats is the right place to break the wall.

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