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, ...
Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...
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 declares the end of pipelines with a unified platform for operational and analytical data
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 ...
With LTAP (Lake Transactional/Analytical Processing), Databricks is introducing an architecture designed to bring operational databases and analytical systems closer ...
Lakebase is a managed Postgres database designed for running AI apps and agents. It adds an operational database layer to Databricks’ Data Intelligence Platform. According to the company, operational ...
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 ...
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