Deepnote vs ML Workspace
Deepnote
deepnote.comML Workspace
mltooling.orgSide by side
| Figure | Deepnote | ML Workspace |
|---|---|---|
| Price from | $3,920/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 1 |
| Spec score · Data Science Platforms | 8.5 (#4) | 8.3 (#7) |
| Encryption | The security overview says data at rest is encrypted with AES 256-bit encryption and data in transit with TLS 1.2 or higher. | SSL/HTTPS can be enabled with supplied certificates or generated self-signed certificates. |
| Integrations | The maker lists built-in integrations including PostgreSQL, BigQuery, Amazon S3, MySQL, Snowflake, GitHub, and dbt. | Listed tools and integrations include Git, TensorBoard, Netdata, Jupyter, JupyterLab, and Visual Studio Code. |
| Product | Deepnote describes itself as an AI workspace for data professionals for data analysis, exploration, and machine learning. | ML Workspace is a self-deployed, web-based IDE for machine learning and data science. |
| Support | Deepnote provides all customers technical support through Intercom and email on weekdays from 9 am to 5 pm Pacific Time as a minimum. | 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
In their own words
Deepnote
Deepnote is an AI workspace for data professionals working on data analysis, exploration, and machine learning. Its copilot can chat with data, make charts, and write code; notebooks can also become dashboards or interactive apps with live data. Teams can collaborate in notebooks, comment on blocks, and share work by link or email invitation. Notebooks can run on hourly, daily, weekly, or monthly schedules, or be deployed as APIs. Listed integrations include PostgreSQL, BigQuery, Amazon S3, MySQL, Snowflake, GitHub, and dbt. Deepnote supports Python, SQL, R, and Stata, with a hybrid execution model and notebook formats including .deepnote, .ipynb, .qmd, .py, and PDF. The free plan allows up to three editors and five projects, with seven-day revision history. Paid pricing starts at $39/user/mo (annual); a 14-day trial is listed. Deepnote says it has SOC 2 Type II certification, encrypts data at rest and in transit, and does not use customer data to improve AI or ML models.
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.