Apache Spark has become the de facto standard for processing data at scale, whether for querying large datasets, training machine learning models to predict future trends, or processing streaming data ...

Spark Declarative Pipelines provides an easier way to define and execute data pipelines for both batch and streaming ETL workloads across any Apache Spark-supported data source, including cloud ...

With the Hydrolix Spark Connector, Databricks users can use the Hydrolix streaming data lake to extract deeper insights faster and cheaper from their real-time and historical log data. According to a ...

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 ...

The cloud-hosted environment, described by Databricks as being deployed by more than 150 firms, aims to simplify the use of the open-source cluster compute engine and cut the time spent developing, ...

Invented eight years ago and intensively commercialized over the past several years, Apache Spark has become a core power tool for data scientists and other developers working sophisticated projects ...

IBM’s support for Apache Spark “throws a huge endorsement to the community and to customers as a way to telegraph what’s next,” said theCUBE cohost John Furrier. At IBM Spark, held in conjunction with ...

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 ...