Five years ago, Databricks coined the term ‘data lakehouse’ to describe a new type of data architecture that combines a data lake with a data warehouse. That term and data architecture are now commonplace across the data industry for analytics workloads.Now, Databricks is once again looking to create a new category with its Lakebase service, now generally available today. While the data lakehouse construct deals with OLAP (online analytical processing) databases, Lakebase is all about OLTP (online transaction processing) and operational databases. The Lakebase service has been in development since June 2025 and is based on technology Databricks gained via its acquisition of PostgreSQL database provider Neon. It was further enhanced in October of 2025 with the acquisition of Mooncake, which brought capabilities to help bridge PostgreSQL with lakehouse data formats.Lakebase is a serverless operational database that represents a fundamental rethinking of how databases work in the age of autonomous AI agents. Early adopters, including easyJet, Hafnia and Warner Music Group, are cutting application delivery times by 75 to 95%, but the deeper architectural innovation positions databases as ephemeral, self-service infrastructure that AI agents can provision and manage without human intervention.This isn’t just another managed Postgres service. Lakebase treats operational databases as lightweight, disposable compute running on data lake storage rather than monolithic systems requiring careful capacity planning and database administrator (DBA) oversight. “Really, for the vibe coding trend to take off, you need developers to believe they can actually create new apps very quickly, but you also need the central IT team, or DBAs, to be comfortable with the tsunami of apps and databases,” Databricks co-founder Reynold Xin told VentureBeat. “Classic databases simply won’t scale to that because they can’t afford to put a DBA per database and per app.”92% faster delivery: From two months to fi …
