Notably, the new Lakeflow Declarative Pipelines capabilities allow data engineers to build end-to-end production pipelines in SQL or Python without having to manage infrastructure.

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

Data + AI Summit -- Databricks, the Data and AI company, today announced it is open-sourcing the company's core declarative ETL framework as Apache Spark™ Declarative Pipelines. This initiative ...

It only took 60 minutes to build this AI agent." The Agent Bricks are now available in beta. Reliable ETL pipelines via drag-and-drop Databricks has also announced the preview of Lakeflow Designer.

Prophecy has launched an integration for Databricks, one that will allow users of the lakehouse to build data pipelines more easily.

After 10 months in preview, DLT is now ready for primetime for production workloads. According to Databricks, the new service will enable data engineers and analysts to easily create batch and ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving engines of insight.

Getting high-quality data to the right places accelerates the path to building intelligent applications," said Ali Ghodsi, Co-founder and CEO at Databricks. "Lakeflow Designer makes it possible for ...

These releases build on Databricks' long-standing commitment to open ecosystems, ensuring users have the flexibility and control they need without vendor lock-in. Spark Declarative Pipelines tackles ...