Databricks adds new SQL Analytics Workspace and Endpoint features, consolidating its acquisition of Redash and bolstering its "data lakehouse" marketing push.

The company achieved a $350 million annual revenue run rate in the third quarter of 2020. With SQL Analytics, Databricks looks to resolve the data warehouse vs. data lake debate in the big data world.

PHILADELPHIA, Nov. 12, 2020 (GLOBE NEWSWIRE) -- Qlik® today announced an expansion of its strategic partnership with Databricks through Qlik’s integration with the newly launched SQL Analytics ...

Fivetran Extends Integration With Databricks, Accelerating SQL Analytics, Data Science and Machine-Learning Applications November 12, 2020 06:00 AM Eastern Standard Time ...

Databricks says that this work, which was based on TPC-DS benchmarks but not TPC-audited, shows Databricks SQL to be 2.7x faster (see the figure below from a Databricks blog post on the subject).

Databricks can run Python, Spark Scholar, SQL, NC SQL, and other platforms. It comes packaged with its own user interface as well as ways to connect to endpoints such as JDBC connectors.

Databricks Lakehouse Platform combines cost-effective data storage with machine learning and data analytics, and it's available on AWS, Azure, and GCP.

ThoughtSpot has expanded the number of backend data sources that can be accessed via its cloud-based analytics platform to include the Databricks cloud service based on the Apache Spark framework ...

In a demo, Ghodsi showed me what the new SQL Analytics workspace looks like. It’s essentially a stripped-down version of the standard code-heavy experience with which Databricks users are familiar.