Apache Spark is a project designed to accelerate Hadoop and other big data applications through the use of an in-memory, clustered data engine. The Apache Foundation describes the Spark project this ...

As well as access control, Databricks 2.0 now offers use of the popular R statistical programming language, support for multiple versions of Spark, and notebook versioning. Spark started in 2009 as a ...

Databricks, the company behind open source Apache Spark, today rolled out a certification program that creates a Spark standard that big data analytic application developers can write to, and that ...

Apache Spark 3.0 is now here, and it’s bringing a host of enhancements across its diverse range of capabilities. The headliner is an big bump in performance for the SQL engine and better coverage of ...

Databricks Inc., the primary commercial steward behind the popular open source Apache Spark data processing framework for Big Data analytics, published a new report indicating the technology is still ...

At a Spark Summit 2017 conference this week, Databricks announced that it will be making an instance of the Apache Spark in-memory computing framework available as a managed cloud service running on ...

The immensely popular open-source cluster computing framework Apache Spark has just reached version 2.0, according to an announcement by the Apache Software Foundation (ASF) yesterday. Spark’s ...

Direct competitors to Databricks Lakehouse Platform include Dremio, Ahana Presto, and Amazon Athena, in addition to the open source project, Apache Spark.

It’s been two years since Apache Spark 1.0 was released, and today Databricks is giving everyone a preview for what is to come in version 2.0. According to the company, the upcoming version ...

Today to kick off Spark Summit, Databricks announced a Serverless Platform for Apache Spark — welcome news for developers looking to reduce time spent on cluster management. The move to simplify ...