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    Wendelin is convergent platform for Big Data and Machine Learning and a variant of ERP5 with extensions for ndarrays, a core module managing RAM beyond physical limits and interfaces with libraries such as scikit-learn, jupyter, pandas, fluentD or embulk. Wendelin is hosted on SlapOS and uses NEO for data storage allowing to manage the data life cycle from ingestion to commercialisation. It is developed and maintained by Nexedi.

    Wendelin Data Sheet

    Wendelin originated from an idea of Jean-Paul Smets and Alexandre Gramfort and was launched by Nexedi at the MariaDB conference in 2014. Thanks to the support of Systematic GTLLPIA, Wölfel and to contributions from Abilian, INRIA, EngieMitsubishi Motors Russia and Paris 13 University, it evolved into a mature, python-native platform for collecting, transforming and visualising streams or batches of data in an industrial context. The Wendelin data hub was jointly developed by Nexedi and Télécom ParisTech.

    Wendelin = scikit-learn + NEO

    Wendelin combines the performance of scikit-learn machine learning with NEO distributed storage in order to provide out-of-core processing of large data sets. Main application fields are industrial big data collection, processing and storage. Any industrial problem of prediction can be adressed with Wendelin: mechanical health prediction, intrusion prediction, power prediction, et al. In addition, the support of other NumPy based libraries such as OpenCV or Pandas, allows Wendelin to be used in other fields such as video processing or finance.


    [2024-01-31] Wendelin 1.0.351 released.

    [2023-02-10] Wendelin 1.0.307 released.

    [2021-03-18] Wendelin 1.0.181 released.

    [2020-12-01] "Is the Big Data era set to transform the wind farm sector?" - Wendelin success story featured in Eureka's site

    [2020-09-23] Wendelin 1.0.162 released.

    [2020-08-04] Lecture: Wendelin Big Data Learning Track released.

    ​​[2019-04-13] Success Case: Predictive Maintenance and Optimisation of Wind Turbines using an open-source Big Data Machine Learning Cloud

    [2018-10-25] Big Data Platform and edge computing using Nvidia TX2 board (PlovdivConf video)

    [2018-11-18] Autonomic anomaly detection of wind turbine structure through GPU based smart sensor (Fraunhofer Institute Industry 4.0 Conference video)

    [2017-11-30] NEO powered Wendelin reaches 100 TB out-of-core data

    [2016-12-21] Wendelin + Jupyter: shared environment in a cluster

    [2016-04-01] Wendelin: 0.5 released - Jupyter Support


    Wendelin is easy to set up and get working. There are two ways to setup Wendelin - Wendelin Standalone  and Wendelin on the cloud. To install wendelin on the cloud follow the Wendelin Big Data Learning Track.


    Source Code


    Automatic tests for Wendelin are run within the Nexedi test environment. The latest test results can be seen in the Nexedi Test Status for Wendelin.


    Nexedi is working with Wendelin on client implementations and research projects. Please refer to the following examples for ideas on how Wendelin can be used:

    Support Services

    Aside from support, consulting and custom development provided by Nexedi, Wendelin can be extended with open source or proprietary components to fit a given vertical big data market.

    The Wendelin project is looking for industrial partners willing to adapt Wendelin to more vertical markets and reinvest part of their revenue into Wendelin core and in particular into scikit-learn.


    Wendelin is Free Software, licensed under the terms of the GNU GPL v3 (or later). For rationale, please see Nexedi licensing.