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MapR Collaborates with SAS to Deliver Big Data Storage Independence


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MapR Technologies, Inc., a provider of a distribution for Apache Hadoop, has extended its support for SAS, a provider of business analytics software and services. According to the vendors, the collaboration between SAS and MapR provides advanced analytics with ease of data preparation and integration with legacy systems, assurance of SLAs, and security and data governance compliance. Additionally, joint customers can cost-effectively grow their big data storage infrastructure without relying on storage area network (SAN) or network-attached storage (NAS).

“The combined SAS and MapR offerings provide joint customers increased flexibility to use the power of advanced analytics in a Hadoop environment,” said David Shamlin, senior director of Research & Development at SAS. “SAS continues to invest in developing our high performance capabilities with Hadoop vendors to ensure customers get the most value out of all their data.”

Through the collaboration, the full scope of technologies in the SAS portfolio, including SAS LASR Analytic Server, SAS Visual Analytics, SAS High-Performance Analytics, and SAS Data Loader for Hadoop will be made available.  MapR integration delivers security and full POSIX compliance for use in “share everything architectures,”  and enables SAS Visual Analytics to easily and securely access all data. With SAS Data Loader for Hadoop, users can prepare, cleanse and integrate data inside MapR for improved performance and then load that data in-memory into SAS LASR for visualization or analysis, all without writing code.

“MapR provides a reliable data store that removes the need for joint customers to rely on SAN or NAS for expansion,” said Steve Campbell, senior director, business development, MapR Technologies.  “This unique benefit provides a compelling solution for SAS users and we look forward to continuing to grow the number of customers deploying Hadoop environments for big data analytics.”

For more information, visit the MapR website.


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