Big Data Specialist MapR Updates Hadoop Distribution with Apache Drill

Big Data Specialist MapR Updates Hadoop Distribution with Apache Drill

The newest version of MapR's Hadoop distribution features Apache Drill for simpler interfacing between NoSQL and SQL data, among other updates.

Open source Big Data vendor MapR expanded the functionality of its Hadoop distribution this week with the announcement of MapR 4.0.1, whose headlining feature is Apache Drill 0.5 integration.

The addition of Drill to MapR's Hadoop distribution introduces ANSI SQL functionality to the platform, which will make it easier for users familiar with SQL interfaces to work with Hadoop and NoSQL data. The upgrade also expands the range of data sources that MapR supports.

MapR partners appear eager to embrace the new technology. Piyush Bhargava of Cisco Systems (CSCO), for instance, said, "As an IT organization serving thousands of Cisco internal users who know SQL, we are excited at the prospects of Apache Drill. Drill's unique approach to do interactive SQL queries without the need for extensions across variety of data types brings together the familiarity of SQL and flexibility of Hadoop together on the scale of Big Data."

The latest release of MapR Hadoop itself also brings the other major Hadoop components up to date, offering MapReduce 1.x and 2.x (YARN), as well as Spark 0.9 and 1.0.2. In addition, HBase is available in versions 0.94.21 and 0.98.4.

MapR hopes that amalgamating the latest open source Hadoop technologies into a single platform will help it prevail in the Big Data wars. "Organizations can now maximize business impact and minimize risk by running operational applications along with real-time analytics on Hadoop,” said Tomer Shiran, vice president of Product Management, MapR Technologies, in reference to the new MapR Hadoop release. "MapR continues to lead the market by integrating the latest open source components into a mission critical, multi-tenant platform with self-healing high availability, disaster recovery and data protection capabilities."

TAGS: Open Source
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