MapR Customer: Gurunavi

Gurunavi Chooses MapR to Strengthen its Big Data Analysis

Gurunavi faced an increasing amount of data, which pushed the limits of its Hadoop-based analysis platform. The company considered system expansion, but was concerned about the anticipated increase in operating costs. Gurunavi therefore decided to upgrade its system architecture and selected the MapR Distribution for Hadoop, an enterprise-grade Hadoop platform with unprecedented dependability and world-record speed, to extend the value of its big data environment. Nautilus Technologies, Inc., a provider of enterprise middle-ware with consulting and development for Hadoop environment,will support deployment of Gurunavi’s new big data system.

Gurunavi selected MapR for several reasons, including:

  • Eliminates single point of failure (SPOF) in Hadoop NameNode — Removing performance bottlenecks, MapR reduces the number of servers required by one third and brings operational efficiencies and reduction in total cost of ownership (TCO).
  • Manages random read and write operations on Hadoop — By leveraging the industry standard NFS interface, MapR seamlessly integrates existing systems with big data analysis infrastructure and runs various file-based applications.
  • Provides multi-tenancy — MapR makes it possible to set respective department policies to ensure smooth operation and management.
  • Preserves job execution — Due to redundancy of jobs across nodes, MapR enables restarting of jobs from the point of failure.

Nautilus is an early adopter of Hadoop and has extensive experience with Hadoop infrastructure design, operation and management. Gurunavi selected Nautilus for its many achievements and to take advantage of its Asakusa Framework™, a development framework for Hadoop, to leverage Hadoop for analytic and business operation purposes.

Nautilus and MapR will work together to help Gurunavi collect and analyze big data, such as access logs and search logs, and plan to provide higher value-added services and greater satisfaction to Gurunavi users and member restaurants.

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Gurunavi Chooses MapR to Strengthen its Big Data Analysis