3DEXPERIENCE Enterprise Data Science vs ML Workspace
3DEXPERIENCE Enterprise Data Science
3ds.comML Workspace
mltooling.orgSide by side
| Figure | 3DEXPERIENCE Enterprise Data Science | ML Workspace |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Science Platforms | 7.3 (#16) | 8.3 (#7) |
| Purpose | Enterprise Data Science solutions turn heterogeneous, multi-source enterprise data into real-time intelligence for faster, better-informed decisions. | ML Workspace is an all-in-one web-based IDE specialized for machine learning and data science. |
| Support | Dassault Systèmes lists 24/7 cloud support for its cloud offers and directs customers to its support portal for product or service issues, including security incidents. | The maintainers say they cannot provide individual support by email and direct users to public support channels; the page lists [email protected] for other requests. |
Plans
3DEXPERIENCE Enterprise Data Science
- Enterprise Data Science rolesPriced on request
In their own words
3DEXPERIENCE Enterprise Data Science
3DEXPERIENCE Enterprise Data Science has no write-up on Specifiction yet; its figures are above.
ML Workspace
ML Workspace is a self-deployed, web-based development environment for machine learning and data science. It brings browser-accessible Jupyter, JupyterLab, Visual Studio Code, and a Linux desktop GUI together, with libraries such as TensorFlow, PyTorch, Keras, and scikit-learn in its main image. Git-related tools include Ungit, Jupytext, nbdime, and a Jupyter extension for pushing notebooks. TensorBoard supports training monitoring, while Netdata and Glances cover hardware monitoring. The workspace can provide a remote runtime for Jupyter, VS Code, PyCharm, Colab, and Atom Hydrogen, typically through passwordless SSH, and can be accessed through a browser, SSH, or VNC. Image options include minimal, R, Spark, and GPU variants; the GPU flavor requires compatible Nvidia drivers and supports CUDA 11.2. Docker is required, with images deployable on Mac, Linux, and Windows. The project describes token or basic authentication and configurable SSL/HTTPS. It is designed for one user, and at least 2 CPUs and 500 MB of memory are recommended for stable use. The free plan costs nothing.