Unbelievable Machine and MapR Technologies expand Partnership

Reseller agreement targets enterprise-class Hadoop projects and cloud services in Germany.

MapR Technologies, Inc. and Unbelievable Machine have announced an expanded partnership agreement. Now an official MapR resale partner, Berlin-based Unbelievable Machine (*um) will provide comprehensive technical and training services in support of the MapR Distribution for Hadoop in Germany.


“The MapR Distribution including Hadoop offers numerous advantages, including scalability for managing extreme data volumes, minimal outage risk with 24/7 use, and real-time processing at world-record speeds,” according to *um founder and CEO Ravin Mehta, “We have been working with MapR since 2012, and use its technology as part of our *umDMR cloud services. The expanded agreement we are announcing today allows us to offer our clients a solution that best fits their very individual needs, depending on their use case and strategy.”


The innovative *umDMR (Dynamic MapReduce) for Hadoop in the cloud allows the dynamic creation of Hadoop clusters via an API or simple command lines from 1 to n nodes. The solution includes a wide variety of standard open source packages including Hive, Pig and HBase and uses a cost effective “billed by resources used” model within the wider *umCloud environment.


“Unbelievable Machine is an exciting and innovative partner and we look forward to our expanded relationship to deliver solutions for a variety of big data use cases for customers across the region,” said Patrik Svanström, VP EMEA, MapR Technologies.


The MapR Distribution including Hadoop is a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. Enabling organisations to successfully leverage the power of Hadoop, MapR provides a secure multi-tenant environment with high availability, disaster recovery, consistent snapshots, and the best in-Hadoop database, MapR-DB, to reliably run both operational and analytical processing in one platform.
 

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