Hex vs ML Workspace
Hex
hex.techML Workspace
mltooling.orgSide by side
| Figure | Hex | ML Workspace |
|---|---|---|
| Price from | $36/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 4 | 1 |
| Spec score · Data Science Platforms | 8.0 (#9) | 8.3 (#7) |
| Integrations | Hex connects to data warehouses, local files including TXT, CSV, JSON, Parquet, Avro, and XLSX, metadata and semantic-layer tools, catalogs, machine-learning tools, and workflow orchestrators. | Listed tools and integrations include Git, TensorBoard, Netdata, Jupyter, JupyterLab, and Visual Studio Code. |
| Security | The Trust Center lists SOC 2 Type II, HIPAA, PCI, GDPR, CCPA, EU-US DPF, Swiss-US DPF, and UK-US DPF badges. | The documentation describes token or basic authentication options and configurable SSL/HTTPS support. |
| Support | The pricing comparison lists email support on Community and Professional, priority SLA support options on Team, and Enterprise SLA support options including Slack and Microsoft Teams where offered. | 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
Hex
Hex is a hosted data platform for exploring data, asking questions, and building data applications through notebooks and conversational self-service. It supports SQL, Python, and R, with real-time collaboration and version history. Users can connect data warehouses and local TXT, CSV, JSON, Parquet, Avro, and XLSX files, as well as metadata, semantic-layer, catalog, machine-learning, and workflow tools. Airflow, Dagster, and dbt integrations can trigger analytical flows and app runs from data pipelines. Hex says its agent grounds answers in organizational context and can connect with Claude, Codex, Cursor, Slack, MCP, a CLI, APIs, or custom agents. Users can build apps from prompts, with code underneath and controls for the finished app. Context Studio and Evals provide visibility into topics, trends, and warnings about answer quality. Community is free; Professional costs $36 a month per Editor, and Team costs $75 a month per Editor. Community and Professional allow up to five published apps, while Team and Enterprise allow unlimited published apps. A 14-day trial is listed.
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.