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Pivotal today announced enhancements to its Pivotal Big Data Suite that improve performance of mission critical, high-scale custom applications with the release of Pivotal GemFire 8.
New features to Pivotal GemFire 8 allow 50% more data per node, improve cluster resiliency, eliminate need for maintenance downtime and allow usage of any programming language through a RESTful API.
As a key component of the Pivotal Big Data Suite, Pivotal GemFire 8 is a distributed in-memory data management solution for enterprises that provides high performance, low latency, extreme scale-out concurrency and consistency for data management and access across globally distributed clusters and nodes. Several thousand customers rely on Pivotal GemFire for large scale web caching to mission critical distributed applications.
The Pivotal Big Data Suite is a subscription based software, support and maintenance bundle consisting of Pivotal Greenplum® Database, Pivotal GemFire, Pivotal SQLFire, Pivotal GemFire XD, Pivotal HAWQ and Pivotal HD. Pivotal Big Data Suite enhancements are now available to current customers with active maintenance agreements.
San Francisco, September 23, 2014 - Pivotal, the company at the intersection of big data, PaaS and agile development, today announced the release of major capabilities in Pivotal GemFire 8. Pivotal’s Big Data Suite includes this new release of Pivotal GemFire, a distributed in-memory data management solution for enterprises creating high-scale custom applications. This advances Pivotal’s mission to make it easy for modern software developers to integrate data to create new classes of enterprise applications.
In today’s business environment, companies are investing in strategic custom applications that provide competitive differentiation and new revenue opportunities. These applications must deliver performance, scale and global reach – while always being “on.” Application developers and IT architects often deal with many terabytes of operational data at global levels of scale in order to meet the highest service level requirements and deliver these business critical applications. They are hampered, however, by out-of-date caching technologies, memory grids and legacy databases.
The Pivotal Big Data Suite provides high performance, extreme scale-out concurrency and consistency for data across globally distributed nodes and clusters. The unique horizontal scale-out architecture of Pivotal GemFire 8 avoids the scaling limitations of traditional databases and scales out across many nodes and clusters. The technology provides low latency response for thousands of concurrent read and write operations on many terabytes of data in-memory.
With the release of the new Pivotal Big Data Suite and Pivotal GemFire 8, applications can now operate with more scale and resilience than ever before. It features:
- In-memory compression: Speed-optimized in-memory compression, allowing individual nodes to manage up to 50% more data per node than before.
- Resilient automation and rolling upgrades: Automatic node reconnection and data restoration and a new ability to serially update software on nodes in a cluster that remains live, eliminating a need for planned downtime for upgrades.
- A new RESTful API: Developers can enhance the performance and resilience of a wider range of high-scale applications such as those developed in Ruby, Scala, or Node.js computer languages.
The Pivotal Big Data Suite is available today to current and new customers. Priced aggressively, the subscription is based on the number of cores on two and three year terms and requires a cumulative contract minimum.
Suneeti Goel, Chief Project Engineer, Centre for Railway Information Systems
“CRIS uses Pivotal GemFire to support high concurrent transactions for reservations and ticket purchases in the newly launched Indian Railways Next generation e-ticketing system. The scalability and resilience features in GemFire have helped us to increase the capacity and availability of our service.”
John Myers, Managing Research Director, Enterprise Management Associates
“EMA research has seen the emergence of in-memory technologies among data management platforms, along with pervasive MPP technology as beginning to erode the boundary between operational systems and enterprise data warehouses and moving these systems toward a more real-time approach. In-memory databases have served real-time applications in finance and defense markets. Now, in-memory solutions are moving into becoming a real-time execution layer for traditional enterprises, as these companies look to innovate with big data. Pivotal GemFire 8, as part of the Pivotal Big Data Suite, is a good example of this movement.”
Hugh Williams, Senior Vice President of R&D, Pivotal
“The release of Pivotal GemFire 8 is a significant advance in the Pivotal Big Data Suite's ability to process and transact high velocity data at significant scale. Higher data capacity, more resilience and the new REST API will help our customers build even more innovative data-driven applications that are strategic for their businesses.”
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