Real-time stream processing isn’t a new concept, but it’s experiencing renewed interest from organizations tasked with finding ways to quickly process large volumes of streaming data. Luckily for you, ...

Apache Spark with Java 8 is proving to be the perfect match for Big Data. Spark 1.0 was just released this May, and it’s already surpassed Hadoop in popularity on the Web. Java 8, the latest version, ...

Streaming data, also called event stream processing, is usually discussed in the context of big data. It is data that is generated continuously, often by thousands of data sources, such as sensors ...

In-memory data grid (IMDG) specialist Hazelcast Inc. yesterday launched a new distributed processing engine for Big Data streams. The open-source, Apache 2-licenced Hazelcast Jet is designed to ...

Five software innovators who were honored in 2018 by a Groundbreaker Award presented by Oracle share their insights into big data and streaming data, the flourishing of open source, and the future ...

The rise and fall of Hadoop. These beliefs helped push Hadoop technologies — an open source distributed processing framework that manages’ data processing and storage for big data.Its stack, formerly ...

Fast, flexible, and developer-friendly, Apache Spark is the leading platform for large-scale SQL, batch processing, stream processing, and machine learning. Topics Spotlight: AI-ready data centers ...

Popular stream processing tools like Apache Flink and Samza require multiple big data services and use Java-based APIs that can be difficult to learn.

A Dice survey shows growing demand for big data skills, and developers—particularly those with Java, mobile and .NET talent—continue to be much sought after.

Stream processing is used to power services such as real-time analytics and alerts, internet of things device tracking, user activity monitoring and online application data serving.