Notice: we’re no longer actively developing Orchest. We could not find a way to make building a workflow orchestrator commercially viable. Check out Apache Airflow for a robust workflow solution.

Build data pipelines, the easy way 🙌

No frameworks. No YAML. Just write your data processing code directly in Python, R or Julia.

💡 Watch the full narrated video to learn more about building data pipelines in Orchest.

Note: Orchest is in beta.

Features

Visually construct pipelines through our user-friendly UI
Code in Notebooks and scripts (quickstart)
Run any subset of a pipelines directly or periodically (jobs)
Easily define your dependencies to run on any machine (environments)
Spin up services whose lifetime spans across the entire pipeline run (services)
Version your projects using git (projects)

When to use Orchest? Read it in the docs.

👉 Get started with our quickstart tutorial or have a look at our video tutorials explaining some of Orchest's core concepts.

Roadmap

Missing a feature? Have a look at our public roadmap to see what the team is working on in the short and medium term. Still missing it? Please let us know by opening an issue!

Examples

Get started with an example project:

👉 Check out the full list of example projects.

Installation

Want to skip the installation and jump right in? Then try out our managed service: Orchest Cloud.

Slack Community

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

License

The software in this repository is licensed as follows:

All content residing under the orchest-sdk/ and orchest-cli/ directories of this repository are licensed under the Apache-2.0 license as defined in orchest-sdk/LICENSE and orchest-cli/LICENSE respectively.
Content outside of the above mentioned directories is available under the AGPL-3.0 license.

Contributing

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

Alternatively, you can submit your pipeline to the curated list of Orchest examples that are automatically loaded in every Orchest deployment! 🔥

Project Name	Stars	Repos Using This	Packages Using This	Most Recent Commit	Total Releases	Latest Release	Open Issues	License	Language
Prefect	12,915	1	138	6 hours ago	225	August 01, 2023	565	apache-2.0	Python
Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines
Tpot	9,213	40	20	23 days ago	61	January 06, 2021	281	lgpl-3.0	Python
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Great_expectations	8,855		35	6 hours ago	236	August 04, 2023	143	apache-2.0	Python
Always know what to expect from your data.
Dagster	8,548		41	6 hours ago	105	September 30, 2022	2,024	apache-2.0	Python
An orchestration platform for the development, production, and observation of data assets.
Pachyderm	5,979		1	12 hours ago	504	August 04, 2023	882	apache-2.0	Go
Data-Centric Pipelines and Data Versioning
Mage Ai	5,572			6 hours ago	278	August 08, 2023	140	apache-2.0	Python
🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data.
Orchest	3,876			4 months ago	19	December 13, 2022	125	apache-2.0	TypeScript
Build data pipelines, the easy way 🛠️
Datascienceresources	3,826			a month ago			20
Open Source Data Science Resources.
Polyaxon	3,387	4	12	a day ago	377	August 14, 2023	122	apache-2.0
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Pipelines	3,293	2	71	20 hours ago	125	July 28, 2023	1,043	apache-2.0	Python
Machine Learning Pipelines for Kubeflow

Orchest