Pentaho open-sourced its Pentaho Kettle Big Data analytic tools to the Apache Software Foundation under an Apache 2.0 license on Tuesday. Pentaho’s decision to open-source Pentaho Kettle is intended to accelerate market adoption of Big Data technologies such as Hadoop and NoSQL according to Matt Casters, founder and chief architect of the Pentaho Kettle Project. Because the Apache Software Foundation incubates the open-source progress of Hadoop and several NoSQL databases, developers now have one organizational infrastructure through which to access Big Data software frameworks and analytic tools such as Pentaho Kettle. Users of Pentaho Kettle 4.3 can leverage Big Data stored using Hadoop HDFS, Hadoop MapReduce, Hadapt, HBase, Hive, HPCC Systems, Cassandra and MongoDB.
Pentaho Kettle 4.3 supports commercial and non-commercial distributions of Hadoop, including “Amazon Elastic MapReduce, Apache Hadoop, Cloudera’s Distribution including Apache Hadoop (CDH), Cloudera Enterprise, EMC Greenplum HD, HortonWorks Data Platform powered by Apache Hadoop, and MapR’s M3 Free and M5 Edition.”
Pentaho Kettle offers users the ability to:
• Import, extract, transform and report on data from a variety of Big Data technologies
• Leverage Pentaho Kettle’s visualization interface to orchestrate jobs such as Hadoop MapReduce jobs, Pentaho MapReduce jobs, Pig scripts, Hive queries and HBase queries
• Make use of its integration with Big Data technologies to take advantage of immanent functionality specific to the relevant Big Data software framework
• Quickly harness the power of the Pentaho Business Analytics full suite of reporting and analytics tools
Pentaho’s decision to open-source Pentaho Kettle 4.3 was widely applauded by the Big Data community. Executives from 10gen, Cloudera and Hadapt hailed the open-sourcing of Pentaho Kettle 4.3 by noting its exceptional analytic capabilities and potential to increase market adoption of Big Data technologies. The open-sourcing of Pentaho Kettle also renders Big Data technologies more widely accessible to the developer community such as users who lack sophisticated coding skills in Java MapReduce jobs and Pig.
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