Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

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 ...

With the official release of Microsoft's latest database offering, let's see what was improved and what still needs some work. Today, at Ignite, Microsoft announced the general availability of SQL ...

Databricks and Snowflake are at it again, and the battleground is now SQL-based document parsing. In an intensifying race to dominate enterprise AI workloads with agent-driven automation, Databricks ...

Vinish Kapoor is an Oracle ACE Pro, software developer, and founder of Vinish.dev, known for his expertise in Oracle. Vinish Kapoor is an Oracle ACE Pro, software developer, and founder of Vinish.dev, ...

Databricks has attracted increasing attention in recent months. Although it is currently a privately held company, it raised a considerable amount of money earlier this year and reported an annualized ...

hi, while it's trivial to run on SQL warehouses, there are cases where scaling of serverless jobs (contrasted to fixed sizes of SQL warehouses), as well as some configurations (dynamic partition ...

Databricks launched Lakebase today, a new database designed for enterprises and developers to build data applications and artificial intelligence agents on a single multi-cloud platform. Lakebase is ...

The company expects $1 billion in revenue run rate for Databricks SQL by the end of its fiscal year in January 2026, a spokesperson said. That’s up from a $600 million run rate in December 2024. Used ...