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Azul Systems and DataStax Partner on High-Performance Java Platform for Cassandra

byadmin
November 5, 2014
in News

Azul Systems, the award-winning leader in Java runtime solutions and DataStax, the company that delivers Apache Cassandra™ to the enterprise, announced a partnership to allow DataStax Enterprise (DSE) customers to leverage the enhanced performance of Azul Zing. Zing is now a certified Java Virtual Machines (JVM) for DataStax Enterprise (DSE), ensuring smooth deployments and seamless operation. In recent benchmark testing, DataStax deployed on Zing outperformed traditional SQL databases by an order of magnitude in both throughput and runtime consistency over conventional JVMs.

Core big data technologies such as Cassandra, Solr and Spark are written in Java requiring a JVM for runtime execution. Azul Zing is the only JVM that implements pauseless garbage collection, providing highly consistent Java runtime performance independent of an application’s memory requirements. Zing is ideal for real-time deployments that need to leverage large in-memory datasets and caches. Through this partnership DataStax customers can now deliver greater business value and provide low latency, real-time solutions for demanding applications requiring an ever-increasing amount of in-memory data such as fraud detection, website personalization, payment systems and time-critical decision support.

“DataStax is the distributed database management of choice for enterprises and together with our partners we offer innovative solutions that complement our technology,” said Matt Rollender, vice president of Infrastructure and Ecosystem Development, DataStax. “We are pushing the envelope with Azul Systems by delivering an incredible boost in performance for JVMs.”

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“Companies depend on real-time big data systems to maximize revenue and mitigate operational risk,” said Scott Sellers, CEO of Azul Systems. “Zing was created to allow Java applications and open source databases like Cassandra to support high throughput, real-time and low latency use cases even with massive in-memory datasets. We are excited to be working with DataStax to bring these benefits to more enterprises.”

Zing is the best JVM for real-time Cassandra deployments. Zing allows Cassandra to operate more consistently by eliminating JVM-caused response time delays. With Zing each Cassandra node can scale to use 1 TB of in-memory data while remaining capable of delivering maximum response times below 20 milliseconds – a level of response time performance unmatched by traditional databases.

To test Zing with your DataStax or Cassandra deployment, request a free evaluation copy here: http://www.azul.com/trial

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(Image Credit: Datastax)

Tags: CassandraDatastaxDataStax EnterprisesolrSpark

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