Free to list, always.No paid rankings. Every recommendation explains its trade-offs.
OpenSourceChoice

Onyxia is a powerful open-source web application designed to streamline the creation of state-of-the-art data science environments. Its core mission is to make advanced cloud-based Key capabilities include UI for launching docker images (Helm charts), Users can define the amount of RAM, CPU and GPU they would like to allocate to their containers, Define environnement variables to be made available in the containers.. Common stack signals: web.

Onyxia upstream project preview
Upstream preview from the project website or source repository. The current interface may differ.

Best for Individuals and small teamsdata ownership and workflow flexibility matter more than a proprietary ecosystem

Skip ifnative integrations with your current suite are essentialMore

Open-source alternative toIndependent open-source project
01

What it is

Onyxia is a powerful open-source web application designed to streamline the creation of state-of-the-art data science environments. Its core mission is to make advanced cloud-based GitHub popularity: 796 stars and 104 forks.

Teams can evaluate Onyxia within its category while keeping the implementation, license, and repository signals visible. Confirm the official documentation against your exact workflow before treating it as a production dependency.

Categories
Productivity
Intended audience
Science And Technology
EU catalogue
Awesome CodeGouvFrStandalone/WebDevelopment
Built with
See repository architecture
02

Who it’s for — and when to skip it

Individuals and small teams

Use it when data ownership and workflow flexibility matter more than a proprietary ecosystem.

Skip if native integrations with your current suite are essential.

Operations teams

Consider it when repeatable workflows can be configured without surrendering data control.

Skip if administration would outweigh the time saved.

Privacy-conscious users

Evaluate it when an inspectable codebase and portable data model are important.

Skip if mobile, offline, or sync behavior is not documented for your devices.

03

Strengths and trade-offs

Why teams consider it

UI for launching docker images (Helm charts)

Users can define the amount of RAM, CPU and GPU they would like to allocate to their containers

Define environnement variables to be made available in the containers.

Source code and MIT license are visible before adoption

Repository metrics are available for independent review

What to validate

A public repository does not automatically guarantee a documented self-hosting path

GitHub popularity is not a security, quality, or product-fit guarantee

The MIT license still needs review against your distribution and commercial model

Support quality, migration effort, and production hardening vary by project

04

Capabilities and stack fit

01UI for launching docker images (Helm charts)
02Users can define the amount of RAM, CPU and GPU they would like to allocate to their containers
03Define environnement variables to be made available in the containers.
04Save and restore your service service configurations.

Catalog metadata supports discovery, not installation. Verify supported versions, dependencies, deployment topology, and production requirements in the official repository.

05

Guides for Onyxia

No project-specific guide is published yet.

Use the learning library to find a guide by technology, category, or difficulty.

Browse guides
06

Approved community reviews

No approved review signal yet.

We do not display synthetic testimonials or ratings without sufficient moderated data.

07

Before you adopt it

  1. 01

    Read the license and confirm it fits your intended use and distribution model.

  2. 02

    Review recent commits, open issues, releases, and the maintainer response pattern.

  3. 03

    Run a small proof of concept with representative data, users, and integrations.

  4. 04

    Confirm whether an official deployment or self-hosting guide exists.

  5. 05

    Document an export or migration path before storing critical data.

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