Dataguise Partners with MapR for Apache Hadoop

Dataguise has partnered with MapR Technologies to create a way tomanage complex data analysis workloads and prevent unauthorized access to data on the Hadoop platform. Under this partnership, DG for Hadoop is now certified for use with the MapR Distribution for Apache Hadoop. This certification also assures data privacy protection and delivers risk assessment intelligence for enterprises using the MapR Hadoop distribution, a win- win deal for both companies.

Dataguise is an innovator of data security intelligence and protection solutions. Apache Hadoop is an open-source software framework that supports data-intensive distributed applications on large clusters of commodity hardware.

MapR is an award-winning Apache Hadoop distributor that offers unprecedented dependability, speed and ease-of-use to Apache Hadoop deployments. It is combined with DG for Hadoop by Dataguise and MapR to enable customers to more confidently and securely harness Big Data for analytics.

"By certifying DG for Hadoop with MapR distributions we are able to protect sensitive information in Big Data environments, enhancing overall security and accessibility," saidManmeet Singh, CEO of Dataguise, in a statement. "Together with MapR, Dataguise helps to deliver on the promise of Hadoop in mission critical environments."

With this partnership, Dataguise will offer diverse organizations within the Hadoop community the ability to expand their reach, ultimately helping customers leverage Big Data through MapR's next generation distribution for Apache Hadoop. DG for Hadoop is a comprehensive, flexible and modular solution that delivers enterprise-class protection to sensitive data aggregated in Hadoop installations.

"Dataguise is actively supporting the security needs of Hadoop environments," said Alan Geary, senior director of business development, MapR Technologies. "Through our partnership, mutual customers of MapR and Dataguise can be assured of regulation compliant delivery of valued data in their Hadoop deployment."

Edited by Ashley Caputo