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MapR Redefines SQL-on-Hadoop With Apache Drill

Distributed ANSI SQL query engine for self-service data exploration and JSON analytics

MapR Technologies Inc. announced the addition of Apache Drill 0.5 to the MapR distribution including Hadoop.

Bringing next-generation ANSI SQL to Hadoop, Apache Drill provides instant, self-service data exploration across multiple data sources including modern applications.

Organizations want to provide access to data stored in Hadoop and NoSQL databases to a broader set of users with existing SQL analysis skills,” said Matt Aslett, research director data platforms and analytics, 451 Research. “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.”

Apache Drill provides the flexibility to immediately query complex data in native formats, such as schema-less data, nested data, and data with rapidly-evolving schemas, with minimal IT involvement. Because SQL queries can run directly on various file formats, live data can be explored as it is coming in, versus spending weeks preparing and managing schemas and setting up ETL tasks. Additionally, Apache Drill supports ANSI SQL so users can leverage their SQL skills and existing investments in business intelligence (BI) tools.

The vision and innovation that the Apache Drill community has brought to the marketplace heralds a new era of data exploration,” said John Schroeder, CEO and cofounder, MapR. “The agility to directly query self-describing data and the flexibility to process complex data types push the envelope in big data analysis and insight.  We are extremely excited by the potential of Drill to transform data-driven companies.

 Organizations that use Apache Drill 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

  • 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 leverage existing SQL skillsets and BI tools to:

  • Minimize switching costs and the learning curve for users via the familiar ANSI SQL syntax

  • Continue using familiar BI/analytics tools such as Excel, Tableau and a host of others using standard ODBC/JDBC drivers

  • Enable ad-hoc/low-latency queries on existing Hive tables. Reuse Hive metadata, hundreds of file formats and user defined functions (UDFs) out of the box.

“As an IT organization serving thousands of Cisco internal users who know SQL, we are excited at the prospects of Apache Drill,” said Piyush Bhargava, engineer, IT Cisco Systems Inc. “It fills in a key gap in our Hadoop architecture, opening up end users to explore data directly. Drill’s unique approach to do interactive SQL queries without the need for extensions across a variety of data types brings together the familiarity of SQL with the flexibility of Hadoop on the scale of big data.

We are very excited about the flexibility and performance Drill promises for ad-hoc data exploration,” said Scott Russman, director, software development at Solutionary Inc. “Enabling additional business units to use our Hadoop big data and correlating across our other big data sources from a single ANSI SQL interface will be incredibly powerful and require very little retooling. This will result in less custom application work and more efficient knowledge sharing throughout the organization.”

We are excited to work with the Apache Drill community in integrating the latest SQL-on-Hadoop technology into the MicroStrategy Analytics Platform,” said Paul Zolfaghari, president, MicroStrategy Inc. “Apache Drill provides an interesting alternative for how we can connect our analytics platform to applications running in big data environments. MicroStrategy looks forward to testing the project in the coming weeks.

Drill enables new and efficient means for querying data stored in Hadoop,” said Dan Jewett, VP of product management, Tableau Software. “We’re excited to see how customers take advantage of this technology in their environments.”

Simba proudly developed the first enterprise ODBC drivers for Hadoop, NoSQL, and big data,” noted Amyn Rajan, CEO, Simba Technologies Inc. “We’re excited to work again with MapR to mark the next milestone: introducing Drill with ODBC 3.8 connectivity. We share with MapR a commitment to open data on Hadoop since we first partnered three years ago. Now, Drill’s support for schema-less data models, best-in-class connectivity, and dynamic SQL means enterprises can easily leverage big data across multiple platforms to their analytic tools, whether they’re using Tableau, Excel, Lumira, or another application.”

Apache Drill 0.5 with the MapR Distribution including Hadoop is available.

 

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