External Plugins

Hop Plugins

The Hop plugins repository contains a collection of plugins that can be used with but can’t or won’t be shipped with Apache Hop.


  • Send information using syslog


  • Dropbox Input

  • Dropbox Output

  • Excel Output

  • Google Analytics

  • Google Sheets Input

  • Google Sheets Output

  • LDIF Input

  • MQTT Input

  • MQTT Output

  • Send message to syslog

Mark Hall


  • CPython: The Hop CPython Project is a plugin for the Apache Hop platform which provides the ability to execute a python script (via the cpython environment) within the context of a pipeline.

  • Hop Machine Intelligence: The hop-mi project is a version of PMI (Plugin Machine Intelligence) for the Apache Hop platform. It (initially) provides access to supervised machine learning algorithms from various underlying "engines". Out of the box, hop-mi provides six engines: Weka, Python scikit-learn, R MLR, Spark MLlib, DL4j (deep learning) and KerasApplication (Keras zoo models backed by TensorFlow). The following learning schemes are supported, and are available in most of the engines: decision tree classifier, decision tree regressor, gradient boosted trees, linear regression, logistic regression, naive Bayes, naive Bayes multinomial, naive Bayes incremental, random forest classifier, random forest regressor, support vector classifier, support vector regressor, multi-layer perceptrons and deep learning networks. hop-mi/PMI is designed to be extensible via the addition of new engines and algorithms.


AtolCD has a github repository with 7 GIS plugins for Apache Hop:

  • Coordinate system operation

  • Geometry information

  • Geoprocessing (between two geometries)

  • Geospatial Group by

  • GIS File input

  • GIS File output

  • Spatial relationship and proximity