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Build data pipelines, the easy way πŸ™Œ

No frameworks. No YAML. Just write Python and R code in Notebooks.


πŸ’‘ Watch the full narrated video to learn more about building data pipelines in Orchest.

Read the docs; get the code; ask us anything!


For a complete list of Orchest's features, check out the overview in our docs!

  • Visually construct pipelines through our user-friendly UI.
  • Code in Notebooks.
  • Run any subset of a pipeline directly or on a cron-like schedule.
  • Easily define your dependencies to run on any machine.

Who should use Orchest?

  • Data Scientists who want to rapidly prototype.
  • Data Scientists who like to work in Notebooks.
  • Data Scientists who are looking to create pipelines through a visual interface instead of YAML.


NOTE: Orchest is in alpha.

For GPU support, language dependencies other than Python, and other installation methods, such as building from source, please refer to our installation docs.


NOTE: On Windows, Docker has to be configured to use WSL 2. Make sure to clone Orchest inside the Linux environment. For more info and installation steps for Docker with WSL 2 backend, please visit

Linux, macOS and Windows

Alternatively, signup for the free-of-charge Orchest Cloud and get a fully configured Orchest instance out of the box!

git clone && cd orchest
./orchest install

# Start Orchest.
./orchest start

Now that you have installed Orchest, get started with our quickstart tutorial, check out pipelines made by your fellow users, or have a look at our video tutorials explaining some of Orchest's core concepts.


The software in this repository is licensed as follows:

  • All content residing under the "orchest-sdk/" directory of this repository is licensed under the "Apache-2.0" license as defined in "orchest-sdk/LICENSE".
  • Content outside of the above mentioned directory is available under the "AGPL-3.0" license.

Slack Community

Join our Slack to chat about Orchest, ask questions, and share tips.

Join us on Slack


Contributions are more than welcome! Please see our contributor guides for more details.