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MapR 5.0 Extends Hadoop for New Class of Real-Time Applications

Extending real-time Hadoop, security, and self-service data exploration and agility

MapR Technologies, Inc. unveiled version 5.0 of the MapR Distribution including Hadoop, extending its lead in real-time Hadoop, security, and self-service data exploration and agility.

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MapR 5.0 is architected for processing big and fast data on a single data platform that enables a class of real-time applications. Organizations are increasingly deploying multiple applications on a single Hadoop Cluster, with 18% of MapR customers deploying over 50 separate applications on a single cluster. The release auto synchronizes storage, database and search indices to support complex, real-time applications to increase revenue, reduce operational costs and mitigate risk. MapR 5.0 includes comprehensive security auditing, Apache Drill support, and the latest Hadoop 2.7 and YARN features.

With the newest release of the MapR Distribution, we continue to lead the market in delivering reliable and real-time Hadoop to the enterprise,” said Anil Gadre, SVP, product management, MapR. “We help enable the ‘as-it-happens’ business where organizations can shorten their data-to-action cycle. Our product is deployed at customer sites and industries that are highly regulated due to their use of sensitive data, which proves that MapR is architected for enterprise-grade security requirements.

Designed as a large-scale batch data analysis system, Hadoop is not often associated with operational analytics or transaction processing,” said Carl W. Olofson, research VP, data management software research, IDC. “Hadoop adds tremendous value for decision management at the strategic and operational levels, but still is emerging as a framework for making tactical decisions ‘in the moment.’ With Hadoop innovations, such as those in MapR 5.0, happening every day, enterprises should consider using Hadoop as a ‘Decision Data Platform’ that functions as a single platform for handling both live operational data and real-time analytics.

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MapR Distribution including Hadoop, version 5.0 feature overview:

  • Extends the MapR real-time, reliable data transport framework, used in the MapR-DB Table Replication capability, to deliver and synchronize data in real time to external compute engines. The first supported external compute engine is Elasticsearch to enable synchronized full-text search indexes automatically without writing custom code.

  • Adds Hadoop 2.7 including YARN 2.7 support to enable features like YARN application rolling upgrades to complement the platform-level rolling upgrades already supported by MapR, as well as integrated Docker container support.

  • Enhances MapR industry-leading data governance and security

      • Comprehensive auditing for all data accesses via log files in JSON format, enabling extensive reporting and validation and quick analysis with Apache Drill. This adds to the trusted security capabilities MapR already provides for authentication and authorization.

      • Support for Apache Drill 1.x, including Drill Views. This innovative feature delivers secure access to field-level data in files to ensure only authorized data can be analyzed by specific analysts. Analysts can be given data governance privileges in which they can share their data sets with other analysts, an important capability for retaining agility in a big data environment.

We are pleased to be working with MapR on integrating their real-time delivery framework with Elasticsearch,” said Jobi George, global partner director, Elastic (Elasticsearch BV). “Customers want search indexes automatically synchronized with the latest data updates. The MapR architecture makes this easier for application developers who need to let their end users search for data almost immediately after it is updated.

Version 5.0 of the MapR Distribution will be available in 30 days.

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