The JBoss Ecosystem is very large and diverse, while you are looking for step by steps and practical introduction to the major JBoss products or looking for tips to improve your business by coupling JBoss Products, this book is for you.
Continue reading “JBoss Developer’s Guide Book is out”
We’re excited to announce the availability of Red Hat JBoss Data Grid (JDG) Version 7.1.
Thanks and congratulations to the JDG engineering and product management team for this release.
JDG 7.1 release focuses on the following areas:
- Performance enhancements
- Apache Spark 2.x integration
- Several other enhancements
Continue reading “What’s new in Red Hat JBoss Data Grid 7.1”
An in-memory data grid is a distributed data management platform for application data that:
- Uses memory (RAM) to store information for very fast, low-latency response time, and very high throughput.
- Keeps copies of that information synchronized across multiple servers for continuous availability, information reliability, and linear scalability.
- Can be used as distributed cache, NoSQL database, event broker, compute grid, and Apache Spark data store.
The technical advantages of an in-memory data grid (IMDGs) provide business benefits in the form of faster decision-making, greater productivity, and improved customer engagement and experience.
Continue reading “Offload your database data into an in-memory data grid for fast processing made easy”
Red Hat JBoss Data Virtualization (JDV) provides several capabilities for caching data including: materialized views, result set caching, and code table caching. These techniques can be used to significantly improve performance in many situations.
Continue reading “External materialized views demystified in Red Hat JBoss Data Virtualization and Red Hat JBoss Data Grid”
We are very excited to announce General Availability (GA) of Red Hat JBoss Data Grid (JDG) 7!
JDG supercharges today’s modern applications and allows developers to meet tough requirements of high performance, availability, reliability, and elastic scale. JBoss Data Grid is compatible with the existing data tier as well as applications written in any language, using any framework and any platform via multiple APIs such as memcached, HotRod, and REST. Red Hat JBoss Data Grid empowers developers to obtain a streamlined approach to standing up new applications, avoiding the challenges normally associated with integrating applications and traditional databases.
JDG 7 introduces the following major new features:
Real-time Data Analytics
- Distributed Streams
JDG 7 introduces a distributed version of the Java 8 Stream API which enables you to perform rich analytics operations on data stored in JDG using the functional expressions available in the Stream API.
- Apache Spark integration
JDG 7 introduces a Resilient Distributed Dataset (RDD) and Discretized Stream (DStream) integration with Apache Spark version 1.6. This enables you to use JDG as a highly scalable, high-performance data source for Apache Spark, executing Spark and Spark Streaming operations on data stored in JDG.
- Apache Hadoop Integration
JDG 7 features a Hadoop InputFormat/OutputFormat integration, which enables use of JDG as a highly scalable, high performance data source for Hadoop. This enables use of tools from the Hadoop ecosystem which support InputFormat/OutputFormat for processing on data stored in JDG.
- Remote Task Execution
Continue reading “Announcing Red Hat JBoss Data Grid 7”