NTT Comware Deploys MapR to Power Hadoop-as-a-Service for SmartCloud®

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MapR Technologies, Inc., provider of a leading distribution for Apache™ Hadoop®, has announced that NTT Comware is using the MapR Distribution including Hadoop to power its new SmartCloud service. Launched earlier this month for customers in Japan, SmartCloud provides Hadoop-as-a-service to leverage its big data processing infrastructure running in the cloud.

NTT Comware, which offers carrier-grade and mission-critical capable cloud and hybrid-cloud services, uses the enterprise-grade MapR Distribution to address the rising need for big data analysis and utilization with high Service Level Agreements (SLAs). NTT Comware based its selection of MapR on a series of benchmarks and proof-of-concept testing they performed in which they compared performance and operability.

MapR offers a truly value-added solution from the other distributions,” said Wataru Imazato, general manager, service provider department, NTT Comware.  “By having a differentiated product that is built from the ground up to address scale, data protection and cost efficiencies, we can offer a Hadoop service in the cloud that meets the requirements for a carrier-grade solution.”

With high availability (HA), mirroring and snapshots, the enterprise-grade MapR Distribution enables NTT Comware to experience higher performance and reliability while using less hardware compared to other distributions. NTT Comware is also able to realize higher cost efficiencies because the MapR Distribution is architected to connect with other systems through a POSIX-compliant, NFS interface and also provides advanced multi-tenancy support.

Top tier companies such as NTT Comware recognize the competitive advantages that MapR brings to the enterprise,” said Steve Fitz, senior vice president, worldwide field operations, MapR Technologies. “Choosing MapR as the basis for their Hadoop service is great validation of the strength of the MapR Distribution and evidence of the continued momentum we have in Japan.”


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