The days of monolithic Apache Spark applications that are difficult to upgrade are numbered, as the popular data processing framework is undergoing an important architectural shift that will utilize ...

Amazon Athena now supports the open-source distributed processing system Apache Spark to run fast analytics workloads. Data analysts and engineers can use Jupyter Notebook in Athena to perform ...

Amazon Redshift integration for Apache Spark makes it easier for developers to build and run Apache Spark applications on data in Amazon Redshift using AWS-supported analytics and ML services.

Unravel Data Introduces AI-powered Data Operations Solution to Monitor, Troubleshoot and Optimize Apache Spark Applications Using Microsoft Azure Databricks ...

Additionally, MapR will release its second free Spark course, Build and Monitor Apache Spark Applications, later in the quarter.

StreamSets, Inc., provider of a DataOps platform for modern data integration, has released StreamSets Transformer, a simple-to-use, drag-and-drop UI tool to create native Apache Spark applications.

With interest in the open source Apache Spark framework for running Big Data applications in real time growing rapidly, IBM this week made it clear that the Apache Spark framework is now a ...

While Spark is orders of magnitude faster than the MapReduce framework it created – and easier to write applications too — there’s no free lunch with Spark, Venkatrao says. “You need to understand how ...

According to Microsoft's benchmarks, .NET for Apache spark programs that do not use UDFs show the same speed as Scala and PySpark-based non-UDF Spark applications.