The best marimo alternatives
The rest of Best Notebook Software, in this site's order: each with what it costs, where it runs and its record score.
It suits people exploring data or developing machine-learning models in hosted Jupyter notebooks, including teams that need shared storage and…
Datalore suits people and teams working with notebooks, databases and shared data reports.
Pluto.jl is designed for students and teachers working with Julia notebooks.
Deepnote suits data professionals and teams working with analysis, exploration, or machine learning who want collaborative notebooks, dashboards, or…
JupyterLab suits people working with notebooks and code in exploratory computing, including data science, scientific computing, computational…
It suits researchers, data scientists, professors, scientists, and library authors who need reproducible notebooks or collaboration across languages.
Colab may suit students, educators, data scientists, AI researchers, and researchers who want to work with Python notebooks in a browser.
Community is listed for hobbyists and small projects, Professional for individuals, Team for companies collaborating on data, and Enterprise for…
SageMath suits students, mathematicians and researchers needing broad mathematical tools across desktop, browser, command-line or self-hosted…
Zeppelin suits people building interactive analytics notebooks with supported languages and data backends.
JupyterLite suits people who want browser-based notebooks or a lightweight REPL without setting up a dedicated application server.
Dnote suits people who prefer terminal-based note capture and locally stored SQLite notebooks.
JupyterHub suits classes, research groups, data science teams, and organizations that need to provide individual computational environments to a…
Observable suits people who want to explore data and explain ideas through interactive code notebooks, alone or with collaborators.
Polynote suits developers and data practitioners who need mixed-language notebooks, Scala, Spark, and local execution.
It may suit teams operating GPU infrastructure for inference, training, fine-tuning, or development workspaces.
