Big Data is boiling away

Pentaho’s new tactic – open Kettle

Chris Mayer

Pentaho wants to be part of the Big Data revolution and puts it chips down – what better way to start than opening up Kettle to the community to gain mass adoption

Pentaho Corporation has announced that it has open sourced all of its big data capabilities in the new Pentaho Kettle 4.3 release, and has moved the entire Pentaho Kettle project to the Apache License, Version 2.0.

This expertly timed move from Pentaho seems to be an attempt to further accelerate the rapid adoption of Pentaho Kettle for Big Data by developers, analysts and data scientists as the go-to tool for operationalising big data. With an Apache License, the link-up with the Hadoop community seems inevitable and would organically grow Kettle’s community.

Pentaho Kettle is an ETL engine (Extraction, Transformation and Loading) and can execute ETL transforms outside the Hadoop cluster or within the nodes of the cluster, taking advantage of Hadoop’s distributed processing and reliability.

Kettle is also the name of the wider project, in which the ETL engine forms the core component. Big data capabilities available under open source Pentaho Kettle 4.3 include the ability to input, output, manipulate and report on data using the following Hadoop and NoSQL stores: Cassandra, Hadoop HDFS, Hadoop MapReduce, Hadapt, HBase, Hive, HPCC Systems and MongoDB.

With regard to Hadoop, Pentaho Kettle makes available job orchestration steps for Hadoop, Amazon Elastic MapReduce, Pentaho MapReduce, HDFS File Operations, and Pig scripts. All major Hadoop distributions are supported 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. 

The benefits to developers from this open sourcing of Kettle appear to be huge. They promise up to 10x increase in productivity through visual tools that eliminate the need to write code such as Hadoop MapReduce Java programs, Pig scripts, Hive queries, or NoSQL database queries and scripts. Making it easier for novices to use Big Data platforms can only be a good thing after all.

Matt Casters, who is the Founder and Chief Architect of the Pentaho Kettle Project spoke about the decision to open source under an Apache license:

In order to obtain broader market adoption of big data technology including Hadoop and NoSQL, Pentaho is open sourcing its data integration product under the free Apache license. This will foster success and productivity for developers, analysts and data scientists giving them one tool for data integration and access to discovery and visualisation.

The linkup with Hadoop specialist Cloudera seems like a natural fit too, as Ed Albanese, Head of Business Development at Cloudera notes:

The Pentaho and Cloudera partnership allows our joint customers to more quickly integrate Hadoop within their enterprise data environments while also providing exceptional analytical capabilities to a wider set of business users. We applaud Pentaho’s decision to open source its big data capabilities under the Apache License; the technology they are contributing is substantial and is a big step forward in helping to accelerate adoption and make it easier to use Hadoop for data transformation.”

It was only a matter of time before Pentaho unleashed Kettle into the wild, and with Big Data set to be the rising star of the year, they’ve timed this move to perfection. We look forward to seeing Kettle’s powerful business analysis tools utilised in an array of Big Data products.

You can download Kettle now and if you’re a beginner to the Big Data field, this video shows you to create a MapReduce job using Pentaho Kettle.

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