The best Jupyter Notebook alternatives fall into four groups: hosted notebooks with free computing for learning, collaborative data notebooks that mix Python and SQL for teams, reactive open source notebooks that run as scripts, and specialist tools for Spark, Scala or data visualisation. Eleven options follow, and most can open the same notebook files you already have.
Jupyter is brilliant for exploring data, but it's less brilliant when three colleagues need the same notebook, results depend on which cell ran first, or a laptop simply isn't powerful enough.
The eleven notebooks below are listed alphabetically and in no particular order, and every description comes from the project's or company's own website, read this week. If SQL is half your work, these ChatGPT prompts for SQL will help whichever notebook you use.
Jupyter alternatives at a glance
I checked the free plan column on each tool's own website, as of Oct 2026. Yes means the site names a free plan, a free version, a free account or an open source version. Trial only means a time-limited trial. Not stated means the pages I read named neither, even where there's a button inviting you to start for free, so check the provider's page before you sign up.
| Tool | Type | Good for | Free plan |
|---|---|---|---|
| Apache Zeppelin | Open source web notebook | Spark and big data teams | Yes |
| CoCalc | Online computing workspace | Projects with files and software side by side | Not stated |
| Count | AI analytics canvas | Checking AI answers on data | Not stated |
| Datalore | Data science notebook from JetBrains | Teams already using JetBrains tools | Not stated |
| Deepnote | Collaborative data notebook | Teams mixing Python and SQL | Yes |
| Google Colab | Hosted Jupyter service | Free GPUs for learning and experiments | Yes |
| Hex | Analytics platform | Sharing analysis with the wider business | Not stated |
| marimo | Reactive Python notebook | Reproducible notebooks that run as scripts | Yes |
| nteract | Desktop notebook app | A notebook that runs on your desktop | Not stated |
| Observable | Data visualisation notebooks | Interactive charts for the web | Yes |
| Polynote | Polyglot notebook | Scala and mixed-language work | Not stated |
Eleven notebooks worth trying
Apache Zeppelin
Best for: Spark users who want an open source, web-based notebook for interactive analytics from the Apache Software Foundation.
CoCalc
Best for: Students and researchers who want an online project space where an agent can build things with their files and software alongside notebooks.
Count
Best for: Analysts who want an AI-powered canvas for analytics and research where every answer can be checked rather than taken on trust.
Datalore
Best for: Data teams already using JetBrains products who want a collaborative notebook for data science from the same company.
Deepnote
Best for: Teams who want a collaborative notebook that mixes Python, SQL and AI, now offered as open source under Apache 2.0.
Google Colab
Best for: Learners and researchers who want a hosted notebook with no setup and free access to computing resources, including GPUs.
Hex
Best for: Data teams who want notebooks, apps and AI agents for analysis that the rest of the business can explore safely.
marimo
Best for: Python users who want a reactive, open source notebook that also runs as scripts and apps, so results stay reproducible.
nteract
Best for: People who want a desktop notebook app for macOS, Windows and Linux instead of working in a browser tab.
Observable
Best for: Analysts and developers who want notebooks with a plain-text file format and free open source tooling, built for data visualisation.
Polynote
Best for: Scala developers who want first-class Scala support and to mix several languages in one notebook while sharing data between them.
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Pick the notebook for the job
- Free computing for learning and experiments: Google Colab.
- Team notebooks mixing Python and SQL: Deepnote or Hex.
- Reproducible notebooks that run as scripts: marimo.
- Spark and big data: Apache Zeppelin.
- Scala and mixed languages: Polynote.
- Charts built for the web: Observable.
Your notebook files aren't locked in
Project Jupyter's nbformat documentation says Jupyter notebook files are simple JSON documents containing text, source code, rich media output and metadata, with each segment stored in a cell.
Because the format is open, your .ipynb files can travel. Before you move a library of work, check that the new tool can open and save that format, and test a notebook with outputs and images rather than a plain one.
Hosted, local or reactive?
Hosted notebooks are quickest to start and handy for sharing, though your data lives on someone else's servers. Desktop apps keep everything local, which some organisations need.
Reactive notebooks rerun the cells that depend on a change automatically. That removes the classic problem of results that only work if you ran cells in a particular order.
Questions to settle first
- Can it open my existing .ipynb files?
- Where will my data and credentials be stored?
- Do I need GPUs, or is a laptop enough?
- Will colleagues edit at the same time?
- Does it connect to our database or warehouse?
- Can I export to scripts or reports?
Signs Jupyter alone isn't enough
- Results change between runs. Try a reactive notebook.
- Colleagues email notebooks around. Use a shared one.
- Your laptop struggles. A hosted notebook adds power.
- You work in Scala or Spark. Pick a specialist tool.
Do you make data notebooks or analytics tools? Tool makers can ask to be considered for a featured place on this list.
My plain advice on moving off Jupyter
Don't migrate everything at once. Pick one live project, move it to the new notebook, and see whether collaboration and reproducibility improve before you change the team's habits.
Keep the open file format at the centre of your choice, so you can always walk away. If you're building a broader toolkit, my roundup of data analytics tools covers what sits around a notebook.
Frequently asked questions
What is the best alternative to Jupyter Notebook?
It depends on your work. Hosted notebooks suit learning, collaborative notebooks suit teams, and reactive notebooks suit people who want reproducible results.
Can other notebooks open Jupyter files?
Many can. Jupyter notebooks are JSON files, and several tools open and save the .ipynb format.
Is there a free alternative to Jupyter?
Yes. Several alternatives are open source or offer free use, including hosted notebooks with free computing resources.
What is a reactive notebook?
A reactive notebook reruns the cells that depend on a change automatically, so results don't depend on the order you ran cells in.
Which notebook is best for teams?
Collaborative data notebooks are built for teams, with shared editing and connections to databases and warehouses.
Do I need a GPU for notebooks?
Only for heavy work such as training machine learning models. Hosted notebooks can provide GPUs for experiments.
