ML Workspace vs MLJAR Studio
ML Workspace
mltooling.orgMLJAR Studio
mljar.comSide by side
| Figure | ML Workspace | MLJAR Studio |
|---|---|---|
| Price from | Free | $20/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 4 |
| Spec score · Data Science Platforms | 8.3 (#7) | 7.9 (#11) |
| Purpose | ML Workspace is an all-in-one web-based IDE specialized for machine learning and data science. | MLJAR Studio is a local AI data workspace for data analysis, machine learning experiments, and Python notebooks. |
Plans
MLJAR Studio
- FreeFree
- Pro$20 a month
- Business$60 a month
- Perpetual license$199, paid once
In their own words
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.
MLJAR Studio
MLJAR Studio is a Python workspace for data analysis, machine-learning experiments, and notebooks, with local-first operation. Ask questions in everyday language and it generates and runs analysis code that remains visible and editable. Its experiment agent can tune models, identify useful features, compare models, track experiments, and produce reports. It works with CSV, Excel, and Parquet files, as well as SQL databases such as PostgreSQL, ClickHouse, and MySQL. Notebook projects can become interactive Mercury web apps hosted on your own infrastructure. Available AI providers include MLJAR AI, OpenAI, Ollama local, and Ollama Cloud; Anthropic and OpenAI-compatible providers are also named. Processing is local by default, but configuring an external provider or MLJAR AI cloud add-on can send data externally. With OpenAI configured, prompts and relevant context may be sent under your settings and provider terms. Plans include Free at free, Pro at $20 a month, Business at $60 a month, and a perpetual license at $199 as a one-time purchase. It runs on Linux, macOS, Windows, and self-hosted environments.