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MapR’s Latest Distribution Gives a Flavour of Apache Drill, With New Developer Pre-Release

by Eileen McNulty
September 18, 2014
in News
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Ushering in the next-generation ANSI SQL to Hadoop, MapR has added a developer pre-release of Apache Drill, coined Drill 0.5, to its latest release.

MapR, one of the leaders in enterprise Hadoop technology for big data deployments, has made available the 4.0.1 version of the MapR distribution including Apache Drill 0.5 on Hadoop 2.4, using YARN. Apache Drill provides “instant, self-service data exploration across multiple data sources” including modern applications, reports a press release on the MapR website.

Matt Aslett the research director of data platforms and analytics, 451 Research informs, “Organizations want to provide access to data stored in Hadoop and NoSQL databases to a broader set of users with existing SQL analysis skills. Apache Drill’s ability to provide access to data in Hadoop without the need for centralized schemas and also to NoSQL datasets with complex data structures including nested and repeated fields differentiates it from traditional approaches to SQL-on-Hadoop.”

According to MapR, Enterprises utilizing Drill can benefit from:

  • High-performance analysis of data in its native format including self-describing data such as Parquet, JSON files and HBase tables
  • Direct querying of data in HBase tables without defining and maintaining a parallel/overlay schema in the Hive metastore
  • Intuitive SQL extensions to query and work with semi-structured/nested data, such as data from NoSQL stores like MongoDB and online REST APIs
  • Queries that simultaneously combine different Hadoop data sources such as files, HBase tables, and Hive tables

Developers and analysts can also mine existing SQL skillsets and BI tools to Minimize switching costs and the learning curve for users via ANSI SQL syntax while use BI/analytics tools such as Excel, Tableau, using standard ODBC/JDBC drivers. It’ll also enable ad-hoc/low-latency queries on existing Hive tables and support reuse of Hive metadata, hundreds of file formats and user defined functions (UDFs), announced MapR.


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With over 40 enterprises and institutions, including Cisco, LinkedIn and the University of Wisconsin coming together since 2012 to contribute to Drill, we can finally see the fruit of their labours.

Read more here.

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(Image credit: MapR)

Tags: Apache DrillHadoopMapRYARN

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