Enterprise data orchestration

Run Hop pipelines on Apache Beam

Large-scale distributed data processing platforms like Apache Spark, Apache Flink, and Google Dataflow make processing huge amounts of data possible. Apache Beam offers a unified programming model to define ETL, batch and stream pipelines on any of these platforms.

Where Apache Beam makes creating a unified code base on all major distributed platforms possible, Apache Hop makes it easy. Hop's visual pipeline development, unit testing and project life cycle support allow data project teams to write pipelines once and run them where it makes most sense.

Upgrade from Pentaho (Kettle)

Apache Hop started its journey in 2019 as a fork of Kettle, the open source project behind Pentaho Data Integration.

Apache Hop and Kettle are different, independent and incompatible projects, this shared history allows Hop to import Kettle projects.

This upgrade not only converts Kettle jobs and transformations to Hop workflows and pipelines, but also gives access to

tons of new functionality including integration with Neo4j and tens of other platforms
projects and environments
run configurations like Apache Spark, Apache Flink and Google Cloud Dataflow through Apache Beam
project life cycle management through integrated version control, unit testing and CI/CD integration

The Apache Hop team just released Apache Hop 2.0.0, the first major release after graduating as a...

The Apache Hop community PMC and community recently released Apache Hop 1.2.0. This release...

Apache Hop 1.1.0 - Apache Hop continues to mature

Apache Hop contains about 4 months of work on 235 tickets by the Apache Hop Community.

Hop...

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Run Hop pipelines on Apache Beam

Upgrade from Pentaho (Kettle)

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Apache Hop 2.0 is available!

Apache Hop 1.2.0 released

Hop 1.1.0 - Apache Hop continues to mature.

Apache Hop contains about 4 months of work on 235 tickets by the Apache Hop Community.

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