MapR 4.0.1 release lets you ‘Drill’ into your Big Data
MapR has just added Apache Drill to its Hadoop distro, giving its customers a new way to use SQL to query their Big Data stores.
The open-source Drill project is one that’s been largely developed by MapR itself. The aim was to create something similar to Google’s own Dremel data analysis tool, which is available through the Mountain View company’s BigQuery service. Unlike Apache Hive or Cloudera’s Impala, Apache Drill does not require users to anticipate queries and set up data models in advance. Rather, they can run interactive ANSI SQL queries against Hadoop and NoSQL data stores, including complex datasets and data in a variety of formats. The list of compatible data sources includes HDFS, Hive, HBase; NoSQL data from MongoDB, REST APIs and other sources, and data from Avro, Parquet and JSON files with nested structures.
“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,” said MapR CEO John Schroeder. “We are extremely excited by the potential of Drill to transform data-driven companies.”
Drill has actually been available as an unsupported “developer preview” for a while now, but today’s MapR 4.0.1 release is the first time it has become a standard part of the Hadoop distro. MapR 4.0.1 will bundle Apache Drill 0.5.0, which is designed to “help enthusiasts start working and experimenting with Drill”, according to its release notes. Drill’s development is based on a monthly release cycle, and version 0.5.0 is said to be a bug-fix update of the previous 0.4.0 release.
MapR’s Hadoop distro now offers no fewer than five different SQL-on-Hadoop technologies for users to query their Hadoop stores. The other options include Apache Hive, Cloudera Impala, Spark SQL and certified integration with Hewlett-Packard Company’s Vertica.
Aside from Drill, MapR 4.0.1 also packs update versions of HBase and Spark. The company said the new edition will be available this week in three editions – M3, M5 Enterprise Edition, and M7 Enterprise Database Edition.
photo credit: Florian F. (Flowtography) via photopin cc
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