Databricks was founded by the people behind Apache Spark, and the company still contributes heavily to the open source Spark project. Databricks has also contributed several other products to open ...

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

Together, these Spark 3.0 enhancements deliver an overall 2x boost to Spark SQL’s performance relative to Spark 2.4. But according to Databricks, on 60 out of 102 queries, the speedups ranged from 2x ...

First created as part of a research project at UC Berkeley AMPLab, Spark is an open source project in the big data space, built for sophisticated analytics, speed, and ease of use. It unifies critical ...

Databricks’ new open-source library enables developers to convert deep learning models into SQL functions. Users can perform transfer learning with Spark MLlib Pipelines and reap the benefits of ...

Unveiled last June, the Apache Spark cloud-hosted platform from Databricks has now opened its doors for business.

With Spark 3.2, the integration with pandas goes up a notch. Folks working in pandas can now scale out their pandas application with a single line change, enabling that app to take advantage of ...

The Spark core supports APIs in R, SQL, Python, Scala, and Java. Additional Spark modules include Spark SQL and DataFrames; Streaming; MLlib for machine learning; and GraphX for graph computation ...

Apache Spark 2.0 is now generally available on the Databricks data platform. The company touts five to 10x performance increases over Spark 1.6 and new support for continuous applications with ...

Databricks and Hugging Face integrate Apache Spark to more seamlessly load and transform data for AI model training and fine-tuning.