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Univa and MapR Technologies Partner to Bring Enterprise-Grade Workload Management to Hadoop Customers

Univa, the Data Center Automation Company and home ofGrid Engine, today announced a partnership with MapR Technologies, the Hadoop technology leader, to integrate Univa Grid Engine with the MapR enterprise platform. The partnership enables customers to leverage the MapR Distribution for Hadoop in conjunction with Univa Grid Engine capabilities of policy control management and infrastructure sharing to run mixed workloads with insightful enterprise reporting and analytics.

“Univa Grid Engine is already a key product in the Big Data infrastructure mix, but with this partnership we are providing customers with integration capabilities to the unrivaled enterprise-class MapR platform for Hadoop,” said Rahul Jain, VP of Big Data, Univa. “This was a natural marriage as MapR provides the most advanced enterprise-grade capabilities for Hadoop, while Univa operationalizes mission-critical applications in mixed workloads to reach its maximum potential and accelerate Hadoop deployments into production.”

The MapR enterprise-grade platform supports a broad set of mission-critical and real-time production uses and brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, databases and streaming applications in one unified Big Data platform. Univa Grid Engine is the most widely deployed, distributed resource management software platform today and supports the new breed of enterprise and Big Data applications that businesses depend on in order to enable successful management in the enterprise data center.

“This announcement is further evidence of the importance of integrating Big Data into enterprise environments,” said Bill Bonin, VP of business development, MapR Technologies. “This partnership lets customers deploy our highly differentiated Hadoop distribution in combination with Univa’s platform, giving customers a compelling, enterprise workload management solution that is flexible and powerful.”

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