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MapR - Global

MapR and Revolution Analytics have teamed to bring R-powered analytics to MapR users.  The combination provides a highly scalable, high-performance environment for data exploration, data visualization, advanced statistics and predictive analytics both in and beside MapR's Hadoop distribution.   

MapR provides a Hadoop environment that considers the needs of IT teams who support it.  Snapshots and volumes allow users to build and test models on the same cluster for production data without impacting operations. This also allows for easy versioning of models and back-testing against historical data sets. In addition, MapR provides a fully read-write data platform which allows existing applications, custom libraries, and modeling languages, and scripts (e.g., Grep, Git) to work out of the box. Moreover, data movement is quick and easy with MapR Direct Access NFS™ without requiring a separate cluster for data ingest.

Revolution R Enterprise (RRE) extends an enhanced and supported version of R with a distributed computing framework, scalable algorithms, big data connectivity tools, an integrated development environment and enterprise deployment tools. RRE does not simply connect to Hadoop like many other analytic tools—it runs inside the MapR Distribution including Apache Hadoop, providing users with direct access to data stored in MapR, guaranteeing enterprise-grade reliability, scale and speed.  Further, Revolution R Enterprise interfaces to popular BI platforms such as Jaspersoft, QlikView or Tableau and productivity tools like Microsoft Excel and Alteryx, quickly transforming results into visual insights that can be shared across the enterprise.

The combination of MapR with Revolution Analytics delivers a combination that ensures your organization has:

  • The Top-Ranked Hadoop Distribution
  • Proven Production Readiness
  • Consistent High Performance
  • Write Once Deploy Anywhere Big Data Analytics

Get the MapR Sanbox for Hadoop

The MapR Sandbox for Hadoop is a fully functional Hadoop cluster running in a virtual machine. Visit