Deepnote Overview
This Deepnote review looks at the collaborative data notebook that has become a serious alternative to Jupyter for teams in 2026. Deepnote treats the notebook as a shared runtime for people and AI agents: SQL, Python, and R live in one document, results render as real tables and charts, and the same project publishes as a data app or scheduled pipeline.
What is Deepnote?
Deepnote is a cloud notebook platform for data teams. Analysts and engineers collaborate in real time on the same notebook, connect to warehouses and databases, and turn analysis into data apps, dashboards, or scheduled runs without leaving the tool. Around the notebook sit the pieces teams usually assemble separately: ETL and ELT pipelines, a data catalog, metric alerts, and a semantic layer that reads dbt models.
The AI story is deep. Deepnote Agent is a project-aware collaborator: in Edit mode it adds, edits, or deletes notebook content, executes code blocks, and adapts as it goes; in Ask mode it answers questions about your data without changing anything. There is also an MCP server for wiring notebooks into external agents and a CLI that converts between Deepnote, Jupyter, Quarto, and marimo formats.
Pricing: Free supports up to 3 editors and 5 projects with limited Deepnote AI and basic machines. Team is $39 per editor per month billed annually, with unlimited viewers and notebooks, premium integrations, scheduled runs, and monthly AI, CPU, and GPU credits. Enterprise is custom. Students and teachers get a near-Team-level Education plan free.
How Deepnote Works
You create a project, connect your data sources, and work in blocks — SQL blocks, Python blocks, charts, and text. Results are inspectable and reproducible, and the open .deepnote YAML format means your work is not locked in a proprietary file. The same artifact can be scheduled, called through an API, connected to Slack notifications, or published as a data app for stakeholders who will never see a cell.
Version control, environment management, and comments are built in, so the notebook behaves like a product rather than a file on someone’s laptop. VS Code, Cursor, and Windsurf extensions let you work locally before scaling to Deepnote Cloud for collaboration and compute.
Who Should Use Deepnote?
Deepnote fits data teams that want notebooks as a shared runtime rather than solo scratchpads — analysts pairing with engineers, teams building recurring data apps, and anyone who needs a project-aware AI agent inside real database context. The Education plan makes it a strong pick for students and teachers too.
It is not for teams whose core output is dashboards and pivot tables — Hex, Mode’s successor, or a BI tool will serve that better. Solo Jupyter power users who run everything locally gain little from the managed workspace, and GPU-heavy training workloads will feel the paid-tier requirement quickly.
Our Verdict on Deepnote
Deepnote is the best notebook for teams in 2026: real collaboration, a genuinely useful AI agent, and a clean path from exploration to scheduled data apps. The free tier is a real workspace, not a demo.
The bottom line of this Deepnote review: if your notebooks are team infrastructure, this is the upgrade — if they are personal scratchpads, Jupyter is still free. Explore more options in our AI Data & Analytics category.
Key Features
- Real-time collaborative notebooks with SQL, Python, and R blocks
- Deepnote Agent: project-aware AI that edits code and answers questions
- One-click publishing from notebook to data apps and dashboards
- Scheduled runs, API execution, and Slack notifications
- ETL/ELT pipelines, data catalog, and semantic layer built in
- MCP server and CLI for agent integrations and format conversion
- Education plan with near-Team features free for students and teachers
Deepnote Pricing
| Plan | Price |
|---|---|
| Free | $0 |
| Team | $39/editor/mo |
| Enterprise | Custom |
Last updated on October 10, 2026 — always confirm on the official site.
Deepnote Pros & Cons
✓ Pros
- Best-in-class real-time collaboration for data teams
- Project-aware AI agent that actually executes code
- Notebook-to-data-app path without switching tools
- Open format and MCP server avoid lock-in
- Education plan is genuinely generous
✕ Cons
- GPU and higher-spec machines require a paid tier — the free plan's basic machines are modest
- Deepnote is not a BI tool; teams needing pivot tables and dashboards should buy purpose-built software
- Compute costs can surprise teams that schedule heavy workloads without watching credits
- Smaller ecosystem than Jupyter, so some niche extensions and community answers are harder to find
Deepnote FAQs
How much does Deepnote cost in 2026?
Is Deepnote free?
What is Deepnote Agent?
Is Deepnote better than Jupyter?
What are the best Deepnote alternatives?
Best Deepnote Alternatives
Count
★★★★☆Count reviewed for 2026 — collaborative data canvases at $34/editor/mo. How the notebook-BI hybrid works, honest pros and cons, and who it's for.
Tellius
★★★★☆Tellius reviewed for 2026 — AI decision intelligence that finds the "why" behind your data with custom pricing. Honest features, verdict, and who it fits.
Airbyte
★★★★☆Airbyte reviewed for 2026 — open-source data integration with 600+ connectors. Cloud pricing from $20/mo, honest pros and cons.
Polymer Search
★★★☆☆Polymer Search reviewed for 2026 — no-code AI dashboards from spreadsheets, no SQL needed. Pricing from $18/user/mo, features, and honest verdict.