Databricks says new products LTAP and Lakehouse//RT unify transactional and analytical data for AI agents, delivering sub-100ms latency and no ETL pipelines.

Many enterprises running PostgreSQL databases for their applications face the same expensive reality. When they need to analyze that operational data or feed it to AI models, they build ETL (Extract, ...

Databricks Inc. today introduced two new products, LakeFlow and AI/BI, that promise to ease several of the tasks involved in analyzing business information for useful patterns. LakeFlow is designed to ...

Since its launch in 2013, Databricks has relied on its ecosystem of partners, such as Fivetran, Rudderstack, and dbt, to provide tools for data preparation and loading. But now, at its annual Data + ...

In this session, we’ll teach you how to build your own Azure Databricks ETL pipeline, starting with ingestion, moving through transformation, and loading your data into a SQL Data Warehouse. Learn ...

Databricks Inc. is using its Data + AI Summit today in San Francisco to unveil a new data architecture designed to eliminate one of enterprise computing’s oldest bottlenecks: the separation between ...

ETL framework is the first to both automatically manage infrastructure and bring modern software engineering practices to data engineering, allowing data engineers and analysts to focus on ...

Databricks announced it is acquiring Mooncake Labs to accelerate its vision of a Lakebase—a new category of OLTP database built on Postgres and optimized for AI agents. With Lakebase, developers gain ...

Databrick’s purchase of startup Mooncake will accelerate the ability of the Lakebase OLTP database to provide data for AI agents and applications. Data and AI platform giant Databricks has acquired ...