Atlas vs Deepnote
An agent that builds,
not a copilot that suggests
Deepnote is a collaborative data notebook with AI assistance. Atlas is an AI agent that does the building — writing and executing reactive notebooks cell-by-cell, with your papers, data, and LaTeX write-ups in the same workspace.
$20/month · Cancel anytime
Side by side
Atlas vs Deepnote, honestly
| Atlas | Deepnote | |
|---|---|---|
| AI model | Agent builds and executes the notebook cell-by-cell while you watch, with an approval gate on file changes | AI assistant suggests and edits code inside blocks you run yourself |
| Notebook engine | Reactive (marimo) — change a cell and every dependent cell re-runs, no stale state | Jupyter-style blocks — execution order is manual, stale state is possible |
| Papers & LaTeX | Built-in .tex editor with live compile and BibTeX, fed by your notebook results | Not built in — export notebooks and write elsewhere |
| PDF & source library | Upload papers, query them with RAG, cite them in your analysis | File uploads without a document knowledge base |
| Knowledge graph | Auto-linked 3D graph connecting notebooks, sources, and notes | Not available |
| Data warehouse integrations | Via Python connectors in the notebook — no native warehouse UI | Native integrations for Snowflake, BigQuery, Postgres and more |
| Collaboration | Workspaces and team plans with pooled AI usage; agent edits require your approval | Real-time multiplayer editing and commenting |
| Pricing | $20/mo individual · $39/seat/mo teams with AI usage included | Free tier · team plans around $39/editor/mo, AI priced separately |
Choose Atlas if
- Your work ends in a paper, memo, or report — not a dashboard
- You want the AI to build and run the analysis, not autocomplete it
- You work from sources: PDFs, filings, papers you need to query and cite
- Reproducibility matters — reactive notebooks can't silently go stale
Choose Deepnote if
- Your data lives in a warehouse and you want native SQL integrations
- Real-time co-editing with teammates is your core workflow
- You're building scheduled notebooks and shared team dashboards
FAQ
Common questions
Is Atlas a Deepnote alternative?
For research workflows, yes. Both are hosted Python notebook platforms, but Atlas centers on an AI agent that builds reactive marimo notebooks and a workspace that includes PDF sources and LaTeX papers. Deepnote centers on collaborative Jupyter-style notebooks with warehouse integrations.
Can I import my existing Jupyter notebooks?
Yes — .ipynb files are converted to marimo's reactive format automatically on upload.
Does Atlas connect to Snowflake or BigQuery?
Not natively. You can query warehouses from notebook code with standard Python connectors, but if warehouse-native SQL blocks are central to your work, Deepnote or Hex fit better.
How does pricing compare?
Atlas is $20/month for individuals and $39 per seat for teams with $25 of AI usage pooled per seat included. Deepnote has a free tier and team pricing around $39 per editor, with AI features priced separately.