Azure Synapse uses a massively parallel processing architecture ideal for enterprise data warehousing, while Databricks leverages Spark’s in-memory processing for real-time analytics and AI ...

In “ Designing a metadata-driven ETL framework with Azure ADF: An architectural perspective,” I laid the groundwork for a scalable, metadata-driven ETL framework using Azure Data Factory (ADF).

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 ...

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 ...

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 ...