MapR Adds Drill to Hadoop Distribution for SQL-Based Big Data Analytics
- By David Ramel
- May 21, 2015
MapR Technologies Inc. added the newly available Apache Drill project for SQL-based Big Data analytics to its Apache Hadoop distribution.
The company this week announced the general availability of the open source Apache Drill 1.0 and its inclusion in the MapR Hadoop distribution.
Drill is a low-latency query engine based on ANSI SQL standards that facilitates self-service, interactive analytics at Big Data scales, including up to petabyte scale (1 PB is equal to 1 million GB). One of its key features is that it doesn't depend on traditional database schemas that describe how data is categorized. Discovering such schemas on the fly makes for quicker analytics, the company said.
MapR engineers including Jacques Nadeau and Steven Phillips have taken the lead on the open source project, which was incubated at the Apache Sofwtare Foundation (ASF) in September 2012 with the goal of wedding the familiar workings of relational databases with the huge new scalability demanded by the Big Data era and the agility of Hadoop systems and their heavy use of NoSQL databases.
"The project has been on the fast track in the last nine months since the developer preview in August 2014, delivering seven significant iterative releases, each adding exciting new features and most importantly, improving on the stability, scale and performance required for broader enterprise deployments," MapR exec Neeraja Rentachintala said in a blog post Tuesday.
In addition to SQL queries, the tool can work with varying types of data, including files, NoSQL databases and more complex types of data such as JSON and Parquet.
"Drill enables interactivity with data from both legacy transactional systems and new data sources, such as Internet of Things (IOT) sensors, Web click-streams and other semi-structured data, along with support for popular business intelligence (BI) and data visualization tools," MapR said in a news release. "Drill provides reliability and performance at Hadoop scale with integrated granular security and governance capabilities required for multi-tenant data lakes or enterprise data hubs."
Upcoming features planned for future editions of Drill include more functionality centered on JSON, SQL, complex data functions and new file formats, Rentachintala said.
David Ramel is an editor and writer for Converge360.