Deepnote alternatives

3 tools to consider instead of Deepnote, shown against it.

Deepnote Project Jupyter Google Colab Observable
Vendor Deepnote Project Jupyter Google Observable, Inc.
Pricing model Free tier + paid plans Open source + paid options Free tier + paid plans Free tier + paid plans
Free tier Yes Yes Yes Yes
Deployment Cloud Cloud, Self-hosted Cloud Cloud, Self-hosted
Open source No Yes (BSD-3-Clause) No Yes (ISC)
Best for Data teams that want a shared, collaborative cloud notebook instead of individually managed local setups. Anyone who wants a free, extensible, self-hostable notebook environment as the base for exploratory analysis. Students, educators, and practitioners who want free, no-install access to GPU/TPU-backed notebooks. Teams and data journalists building custom, interactive, web-native charts and dashboards.
Pricing

Free plan for small teams with limited projects and AI usage; Team plan bills per editor per month with monthly AI/compute credits, Enterprise is custom.

Free $0
Team $39/editor/month billed yearly
Enterprise custom

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Free and open source; Project Jupyter does not sell a hosted product or support plan.

Pricing has not been verified yet — see the vendor's site.

Free tier with limited, non-guaranteed GPU/TPU access; paid Pro and Pro+ monthly subscriptions and pay-as-you-go compute units add faster accelerators and longer runtimes.

Pricing has not been verified yet — see the vendor's site.

Observable Framework is free and open source and can be self-hosted anywhere; Observable Cloud adds paid hosting, collaboration, and access-control plans.

Pricing has not been verified yet — see the vendor's site.

Features
  • Real-time multi-user notebook collaboration with comments
  • SQL blocks alongside Python cells in the same notebook
  • Built-in AI assistant for code generation and explanation
  • Shared, reusable data source connections across a workspace
  • Scheduled and background notebook execution
  • One-click publishing of notebooks as reports or apps
  • Version history and revision recovery
  • Interactive notebook combining code, output, and Markdown narrative
  • Language-agnostic kernel protocol (Python/IPython, R, Julia, and more)
  • JupyterLab IDE-style interface with file browser, terminal, and extensions
  • JupyterHub for multi-user, self-hosted deployments
  • Widgets (ipywidgets) for interactive controls inside notebooks
  • nbconvert for exporting notebooks to HTML, PDF, and slides
  • Large third-party extension and kernel ecosystem
  • Zero-setup Jupyter notebooks in the browser
  • On-demand GPU and TPU access
  • Google Drive-based storage, sharing, and version history
  • One-click GitHub notebook import/export
  • Real-time collaborative editing
  • Background execution for long-running jobs (paid tiers)
  • Pay-as-you-go compute units for occasional heavy use
  • Reactive cells that auto-update when dependencies change
  • Data loaders that run Python, SQL, R, or JavaScript to produce page data
  • Deep integration with D3.js for custom interactive visualizations
  • Static-site output that can be hosted on any static host
  • Observable Cloud for managed publishing, refresh, and access control
  • Large public library of shared community notebooks

In the index now