Invest in leading Hadoop technology to deploy the broadest set of big data applications.


Analytics and Operations on One Platform

MapR allows you to do more with Hadoop including data storage and transformation, data exploration and analytics as well as light-weight OLTP transactions. MapR supports a wide variety of workloads with dynamic workload management, data placement control and multi-tenancy.

Mission Critical Applications

Support mission critical applications at 99.999% availability. Run a lights-out data center with self-healing of all critical services, data protection, disaster recovery, rolling upgrades as well as instant recovery of operational database applications.

Easy BI and Data Warehouse Integration

Leverage industry standard interfaces such as NFS and ODBC to connect different data sources seamlessly. Create new business intelligence workflows that include Hadoop while continuing to use existing scripts, applications and data transformation tools.


Enterprise Data Hub:

Best ROI

Supported by MapR Distribution’s world-record setting performance, run your cluster at 2-5 times better performance than other distributions. Better hardware utilization provides you with the fastest ROI.

Proven Cloud Deployment

Deploy Hadoop in the cloud or in a hybrid-cloud setup with industry leaders such as Amazon Web Services and Google Compute Engine. MapR has proven advantages over other Hadoop distributions in the cloud and is natively available on AWS.

No Vendor Lock-in

MapR delivers full binary compatibility and support for industry standard APIs for Hadoop and beyond, as well as the ability to port data in and out of the distribution without any code changes or lock-ins.

World-Class Support

MapR offers a full range of SLAs to match your business needs. The combination of world-class support engineering, thorough documentation and vibrant forums ensures smooth operations of your mission critical applications.

Need help on getting started with big data and Hadoop? Check out The Executive's Guide to Big Data & Hadoop  by the author of "Hadoop for Dummies".
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