Pivotal Scales GemFire In-Memory Database Capacity With Latest Release

Speed-optimized compression codec called Snappy credited with the capacity increase

John Rath

October 1, 2014

1 Min Read
Pivotal Scales GemFire In-Memory Database Capacity With Latest Release
Paul Maritz,CEO, Pivotal, speaking at an industry event. (Source: Pivotal’s Facebook profile)

Pivotal announced a new release of its GemFire distributed in-memory database, which is part of its Big Data Suite. Pivotal GemFire was formerly known as VMware vFabric GemFire.

GemFire 8 scales across nodes and clusters and responds to thousands of concurrent read and write operations on many terabytes of data, the company said. With advances in the new release, nodes can manage up to 50 percent more data per node than before. Much of the increase in capacity comes from an appropriately named algorithm called Snappy -- a speed-optimized compression codec.

A new RESTful API allows developers to enhance performance and resilience of a wider range of high-scale applications, such as those developed in Ruby, Scala or Node.js languages. Other new features include node reconnection and data restoration and an ability to serially update software on nodes in a cluster that remains live, eliminating a need for planned downtime for upgrades.

GemFire 8 uses distributed commodity hardware in a 'share-nothing' architecture. Although configurable, it emphasizes partition tolerance and consistency over availability of data, Pivotal's enterprise software marketing executive Gregory Chase pointed out. Product features that help balance the need for availability of nodes include node failover to replicas in the event of system failure or network partitioning and the ability to run multiple clusters connected via a WAN, giving you multi-site disaster recovery capacity.

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