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I'm happy to share that Red Hat was named a Strong Performer in The Forrester Wave™: In-Memory Databases, Q1 2017. I believe that this is a great recognition for the versatility and flexibility of Red Hat’s in-memory data management offering, Red Hat JBoss Data Grid, which was also recognized as a Leader in The Forrester Wave™: In-Memory Data Grids, Q3 2015. I believe that being recognized in both the IMDG and IMDB evaluations speaks to the versatile capabilities that JBoss Data Grid can offer customers to help them simplify the delivery of strategic and demanding data initiatives. We have seen customers around the globe choose JBoss Data Grid for a variety of use cases, such as scale-out NoSQL database, high-performance big data analytics and compute grid, real-time data event processing, and elastic state store for hybrid cloud applications.
The explosion of data and the rise of analytics as a core business function have helped pave the way for in-memory computing, and, in particular, data grid platforms, to move more into the mainstream as a way to help better address the performance and scalability challenges from big data, the Internet of Things (IoT), and the need for real-time insights.
This level of performance and scalability can often exceed what enterprise IT has historically been able to provide, and organizations can take a new approach to analytics and building a new generation of intelligent applications based on in-memory technologies that are able to more quickly turn data into insights, and insights into actions. Time-to-insight-to-action can help to make or break a business in an increasingly digital world. This new generation of applications can provide contextual intelligence — the ability to analyze live data and react automatically with guided decisions. In-memory data management platforms such as JBoss Data Grid can deliver insights on perishable business opportunities before the moment is lost.
With customers expecting increasingly personalized experiences and the emergence of the IoT, companies need to be able to meet this expectation by being able to quickly make sense of rapidly changing data and taking immediate action. Enabled by in-memory computing technology, contextual intelligence can track fast-changing data streams within live systems, enrich them with historical data, and analyze them in parallel. It can then provide actionable feedback that identifies opportunities and help steer behavior so organizations can capitalize on perishable business insights and opportunities. The benefits of contextual intelligence can be applicable to a range of industries, including financial services, manufacturing, telecommunications, utilities, retail, and more.
As noted by Forrester in the IMDB report, "Red Hat offers a scalable in-memory data grid to build high-performance apps. Red Hat JBoss Data Grid comprises a distributed cache and a NoSQL Database technology that delivers a peer-to-peer, no-master/slave architecture designed to scale to hundreds of nodes on commodity hardware. It supports transactional capabilities with configurable full ACID compliance and durability using data replication across servers and data centers. JBoss Data Grid integrates with Apache Spark to support real-time analytics, and it has broad security, offering role-based access control, node authentication, column-masking, and encryption. The database runs on AWS, Azure, and Google Cloud and uses the OpenShift Container platform for private cloud."
The unified capabilities of Red Hat JBoss Data Grid can bring many of the benefits of parallel supercomputing to the enterprise and can deliver a new generation of advanced in-memory analytics and stream processing capabilities that enable contextual intelligence to all business operations.