Announcing Lakehouse//RT | Databricks Co-founder and Chief Architect Reynold Xin at Data + AI Summit
Summary
Lakehouse//RT is a new Databricks warehouse product, powered by the Raiden engine, designed for read-only workloads with millisecond performance and massive concurrency. It allows users to query Delta or Iceberg data directly on their data lake, governed by Unity Catalog, potentially collapsing separate serving stacks into a single platform.
Summary generated by brickster.ai from the video transcript.
More from Databricks
EventsIntroducing CustomerLake: The Agentic CDP | Ali Ghodsi Databricks CEO at Data + AI Summit
Databricks introduces CustomerLake, an agentic Customer Data Platform built on the lakehouse architecture. It features a profile agent for identity deduplication using LLMs and a campaign agent for personalized, one-to-one "infinity campaigns."
EventsRecap of product announcements from Data + AI Summit 2026 | Day 1
Databricks announced several new products and features at the Data + AI Summit 2026, Day 1, including the Genetic Data Foundation, Lakehouse RT, Lake Base with disaster recovery, Lake Flow, Genie Ontology, Unity AI Gateway, Omnigent, and various Genie agents (Genie 1, Genie Code, Genie Agents). They also introduced new applications like Lake Watch for SIM and Customer Lake for CP.
EventsGenie Ontology an automatic and secure context store | Data + AI Summit 2026 #databricks
Genie Ontology is a new Databricks feature that automatically connects to all organizational data, including external sources like Google Drive and email. It constructs a graph of important knowledge in the background, making this context available for AI agents.
EventsHow to make AI work in the enterprise | Ali Ghodsi Co-founder and CEO of Databricks
Databricks aims to enable enterprises to integrate AI by providing organizational data, processes, and human knowledge as context to AI models. This contextualization allows existing smart AI models to solve many enterprise tasks effectively.
EventsLTAP - Lake Transactional/Analytical Processing a new data architecture that unifies OLAP and OLTP
LTAP (Lake Transactional Analytical Processing) is a new data architecture that unifies OLAP and OLTP storage, eliminating data copying and pipelines. It allows a single copy of data for both transactional and analytical systems, built on open formats like Postgres, Delta Lake, and Iceberg, without compromising performance.