For those needing robust ELT, data science, and machine learning features within a data lake/data warehouse framework, Databricks is the winner. Azure ML wins for those just wanting to add ML to ...

Azure Synapse: Best for unified data analytics across big data systems and data warehouses. Databricks: Best for use cases such as streaming, machine learning, and data science-based analytics.

The Azure Databricks service is supposed to give them an easier experience of running big data jobs than rolling their own Spark deployment, and offers a deeper level of compatibility with ...

Databricks has unveiled a new extract, transform, load (ETL) framework, dubbed Delta Live Tables, which is now generally available across the Microsoft Azure, AWS and Google Cloud platforms.

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 ...

Recently, Prophecy released Data Copilot, which harnesses generative AI and large language models, streamlines data pipeline creation and acts, essentially, as an AI data assistant.

Because this is essentially a first-party Azure service, users will also get all of the usual Azure SLAs and be able to deliver support to their joint customers — a group of Databricks engineers ...

Microsoft Azure customers interested in parsing large amounts of data to improve their businesses will soon be able to use Azure Databricks, developed in consultation with big data startup ...