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

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

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 ...

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

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 ...

Hydrolix, the company transforming the economics of log data with its streaming data lake platform, is unveiling a new Apache Spark connector that democratizes the power of Databricks to customers' ...

Big data startup Databricks keeps humming along, announcing on Monday a large round of venture capital and a new cloud service that aims to seed adoption of Spark -- a framework it says is faster ...

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 ...

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 ...