An experimental environment for executing a Kettle transformation as a Storm topology.
Pentaho has lead the big data ETL space for 3 years by providing ETL developers a visual environment to design, test, and execute ETL that leverages the power of MapReduce. Now with Kettle for Storm, that same ETL developer is immediately productive with one of the most popular distributed streaming processing systems today: Storm. Any existing Pentaho ETL transformations can be executed as realtime processes via Storm - including those used in Pentaho MapReduce. This powerful combination allows an ETL developer to provide data to business users when they need it most without the delay of batch processing or overhead of designing additional transformations.
Pentaho ETL begins processing data as it arrives from the source and produces the valuable data sets your business depends on immediately. Get up to the second insight for your key business metrics by reacting when data arrives and delivering real-time dashboards, reports, or intermediate data sets to be used by your existing applications.
Many of our customers have long running batch Pentaho ETL jobs that run within Hadoop via MapReduce. Pentaho for Storm compliments these by allowing developers to reuse existing transformations to process data immediately. Both batch and real time workflows are powered by Pentaho ETL, empowering existing developers to build upon years of knowledge to learn the most from their data, instantly.
Kettle for Storm allows Pentaho ETL developers to reuse their knowledge and beloved Kettle components to process data differently. Deliver data when its needed - all with a familiar tool set. Looking for additional tools for your Pentaho ETL tool kit? Check out the Kettle Marketplace!
Today, Kettle for Storm can process many of your existing transformations but this wouldn't be in Pentaho Labs if it were complete. We're continuing to build out support for the entire Kettle ecosystem of steps:
Steps that do not emit at least one message for every input: