Deepnote

Deepnote is a collaborative data notebook platform that combines Jupyter compatibility, real-time collaboration (like Google Docs for code), warehouse integrations, and an AI assistant. Data scientists, analysts, and ML practitioners use it for exploratory analysis, reporting, and model prototyping without the infrastructure overhead of self-hosted JupyterHub.

Yes. Deepnote offers a genuinely useful free tier for individuals that includes unlimited personal notebooks, basic integrations, and AI assistance. The Team plan at $31/user/month adds real-time collaboration, scheduled runs, warehouse connectors, and shared workspaces. Enterprise tiers add SSO, audit logs, and larger compute through custom contracts.

Deepnote is the most Jupyter-like of the three — real-time collaborative notebooks that feel familiar to anyone who's used Jupyter. Hex is more ambitious with its Magic AI, app-publishing features, and notebook-to-dashboard workflow. Mode is the most BI-oriented, SQL-first with polished dashboards. Pick Deepnote if you want collaborative Python notebooks; pick Hex if you want AI-first analysis apps; pick Mode if you want SQL and dashboards.

Deepnote has native connectors for Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL, MongoDB, ClickHouse, Athena, and most major analytics warehouses. Connections are encrypted and credentials are stored securely per workspace. Queries execute on the warehouse side, and results can be loaded directly into pandas DataFrames for further Python analysis.

Deepnote AI can generate Python or SQL from natural language prompts, explain existing code, suggest fixes for errors, create charts from plain-English descriptions, and help with debugging. It's useful as a pair programming assistant for analysts who want to move faster without losing control of their notebooks. The assistant respects the execution context of the notebook and has access to the schemas of connected warehouses.

For most use cases, yes. Deepnote supports the full Jupyter notebook format, so you can import .ipynb files directly and continue working. You gain collaboration, managed kernels, integrated warehouse connections, and AI assistance. You lose full control over the kernel environment and some advanced Jupyter extensions. For teams already running self-hosted JupyterHub, Deepnote is often a welcome reduction in infrastructure burden.

Yes. Deepnote is SOC 2 compliant and Enterprise plans add SSO, SAML, SCIM, audit logs, and dedicated infrastructure options. Warehouse credentials are encrypted at rest, and queries respect the permissions of the connecting user. For teams that need full isolation, Enterprise offers dedicated cloud environments with private networking.