Dataguise has recently formed a partnership with MapR Technologies to manage complex data analysis workloads and prevent unauthorized access to data on 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. This is win- win deal for both companies.
Dataguise is an innovator of data security intelligence and protection solutions.
MapR is an award-winning Apache Hadoop distribution, which offers unprecedented dependability, speed and ease-of-use to Apache Hadoop deployments. It is combined with DG for Hadoop by Dataguise, MapR enables 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," said in a statement, Manmeet Singh, CEO, Dataguise. "Together with MapR, Dataguise helps to deliver on the promise of Hadoop in mission critical environments."
Apache Hadoop is an open-source software framework that supports data-intensive distributed applications on large clusters of commodity hardware.
With this partnership, Dataguise will be able to offer diverse organizations within the Hadoop community a way to expand their reach and ultimately help 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."
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Edited by Brooke Neuman