Announcing Red Hat JBoss Data Grid 7.0

Red Hat JBoss Data Grid 7.0 is here.

This significant new release offers a variety of features which are designed for complex, distributed, and high-volume, velocity data requirements. JBoss Data Grid can support both on-premise and cloud-based infrastructures, and it can handle the near-instantaneous, complex demands of Internet of Things and big data environments.

What It Brings

JBoss Data Grid can be deployed in different architectures, depending on the needs of your environment. In addition to the traditional usage as distributed cache, in-memory data grids can function as the primary data store for applications or as a compute grid for distributed computing.

Data Storage

There are two use cases for using JBoss Data Grid as a data store:

  • Data caching and transient storage. As an in-memory data store for frequently accessed application data or for transient data, such as shopping cart information or session data. This avoids hitting transactional backend systems are frequently, which reduces operating costs.
  • Primary data store. Data Grid can function as a key-value store similar to a NoSQL database. This can be the primary data source for applications for rapid retrieval of in-memory data and to persist data for recovery and archiving. Applications can run data-intensive operations like queries, transaction management, and distributed workloads.

Computing Grid

Modern architectures require flexible, distributed, and scalable memory and data storage. Using JBoss Data Grid as a distributed computing grid can help support the most demanding architectures:

  • Scale-out compute grid and event-driven computing. Through storage node clusters, JBoss Data Grid can do a distributed architecture with application logic at each node for faster data processing and lower latency and traffic. This architecture also supports event-driven computing by executing application logic at the node as data are updated.
  • Big data and the Internet of Things. JBoss Data Grid can support massive data streams — hundreds of thousands of updates per second. The Internet of Things can have data streams from thousands of connected devices, updating frequently. Clustering and scale, application logic and processing, and both in-memory and persistent storage in JBoss Data Grid enable those big data architectures by managing those massive data streams.

Real-Time Analytics and Performance for Digital Business

DIgital transformation means that organizations are pushing into a new intersection between their physical goods or services and online, on-demand applications. This digital environment is reliant on data — and unlike previous generations, this technology uses -near live data streams rather than historical data collections.

JBoss Data Grid is a leading high-performance, highly-scalable, in-memory data grid. In-memory data grids provide a means of scalable memory so that even rapidly changing application data can be processed.  Better data processing and management enables organizations to make fast, accurate decisions using large data streams. JBoss Data Grid 7.0 offers a data foundation for real time analytics:

  • Low latency data processing through memory and distributed parallel execution
  • Data partitioning and distribution across cluster nodes for horizontal scalability
  • High availability through data replication
  • Shared data services for real-time and in-memory analytics and event processing

A Short List of Major Features

The release notes cover the full features and enhancements for JBoss Data Grid 7.0. There are a number of features for improved ease of use, real-time analytics, and language support:

  • Distributed streams, which uses the Java 8 Stream API to take complex collections of data and run defined analytics operations.
  • Resilient distributed dataset (RDD) and DStream integration with Apache Spark 1.6, allowing Data Grid to be a data source for Spark and to execute Spark and Spark Streaming operations on data in Data Grid.
  • Hadoop InputFormat/OutputFormat integration, so that Hadoop tooling and oeprations can be used with data stored in Data Grid.
  • New administrative consoles for cluster management to simplify common tasks for managing the cache, nodes, and remote tasks.
  • Control operations for clusters including graceful shutdowns and startup and restores from persistent storage.
  • A new Node.js Hot Rod client to support using Data Grid as a NoSQL database with Node.js applications.
  • Running remote tasks (business logic) on a Data Grid server from the Java Hot Rod client.
  • Support for a Cassandra cache store, which persists the entries of a distributed cache on a shared Apache Cassandra instance.

Additional Resources

Announcing Red Hat JBoss Data Grid 7.0 Beta

We are very excited to announce availability of Red Hat JBoss Data Grid (JDG) Version 7.0 Beta!

Based on the Infinispan project, JBoss Data Grid is a leading high-performance, highly-scalable, in-memory NoSQL store, which enables your enterprise to make fast, accurate decisions on large volumes of changing data and provides superior user experience for your customer-facing applications.

JDG 7.0 Beta introduces major new features in the areas of Real-time Data Analytics, ease of use and administration, and expanded polyglot support.

Real-Time Data Analytics

  • Distributed Streams: In JDG 7.0, we introduce 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 and Hadoop Integration: JDG 7.0 features a new Resilient Distributed Dataset (RDD) and 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. We have also added a Hadoop InputFormat/OutputFormat integration, which enables use of tools from the Hadoop ecosystem on data stored in JDG.
  • Remote Task Execution: JDG 7.0 features the ability to execute tasks (business logic) on a JDG server from the Java Hot Rod client. The task can be expressed as a Java executable loaded on the JDG server or as a stored JavaScript procedure which executes on the Java 8 (Nashorn) scripting engine on the JDG server.

Ease of Use and Administration

In JDG 7.0, we have released a new administration console which enables you to view a JDG cluster and perform clustered operations across its nodes. Operations include creating new caches and cache templates, adding or removing nodes, and deploying or executing remote tasks. We have also added the ability to shut down or restart a cluster in a controlled manner, with data restore from persistent storage.

Expanded Polyglot Support

Node.js Hot Rod client: JDG 7.0 introduces a new Node.js (JavaScript) Hot Rod client, which enables you to use JDG as a high performance distributed in-memory NoSQL store from Node.js applications.

Cassandra Cache Store

Additionally, JDG 7.0 introduces a new out-of-the-box Cassandra cache store, which enables you to persist the entries of a distributed cache on a shared Apache Cassandra instance.

Try It Today

Red Hat JBoss Middleware customers can download JDG 7.0 Beta from the Customer Portal

Beta documentation, including release notes, is available on the documentation page in the Portal.

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