marimo

marimo is an open-source notebook environment for Python and SQL, aimed at people who want exploratory work to behave more like a reproducible software project. Its strongest case is the combination of reactive execution, Git-friendly files, and paths from notebook to app or script.

Overview

Analysts, data scientists, engineers, educators, and web developers can use marimo for experiments, data work, and interactive applications. It is a particularly good fit when Python is the team’s working language and notebook outputs need to stay consistent with code; it is less compelling for work centered on other languages.

Key features

When a cell runs, marimo runs dependent cells or marks them stale. That is a meaningful safeguard against outputs silently reflecting an earlier version of the code. Deterministic execution and package requirements stored with notebooks add to the reproducibility case, but do not make arbitrary notebook code safe to run.

Notebooks are pure Python files that can be versioned in Git, run as scripts, and reused as modules. They can also be deployed as interactive web apps or executed in a browser through WebAssembly. That range supports a workflow beyond exploratory analysis, though it also makes marimo a Python-centered choice rather than a general-purpose, multi-language notebook.

Sliders, dropdowns, interactive dataframe tables, and selectable plots give collaborators ways to explore results without changing code. SQL cells work with dataframes, CSVs, Google Sheets, and databases, with integrations including Polars, Pandas, PyArrow, DuckDB, SQLite, Postgres, and MySQL. AI notebook features support OpenAI, Anthropic, Gemini, Ollama, and OpenAI-compatible APIs. These options are useful for teams already working with those tools, while the core appeal remains the notebook’s Python workflow.

Developers can use the VS Code extension in VS Code, Cursor, and other VS Code forks, or use the PyCharm plugin. Project package management supports pip, uv, Poetry, Pixi, and Rye; notebook sandboxes support uv and Pixi. Installation guidance also includes conda.

Security requires judgment. marimo says code does not run without explicit user action, and notebooks opened in edit mode are statically loaded rather than executed as Python modules. Remote edit mode enables token authentication by default, while run mode supports token flags or custom middleware. Running a notebook can still execute arbitrary code, so this is not a reason to trust an unknown notebook.

Pricing

marimo open-source notebook — free. The free, permissively licensed software is the natural choice for individuals and teams who can manage their own environment. It gives up hosted convenience in favor of running the open-source notebook themselves.

molab — free. The hosted option includes 4 CPUs, 32 GB RAM, and sessions of up to 12 hours, with use described as free while reasonable. It suits people who want cloud notebooks without arranging their own runtime, but notebooks are public by default. For notebooks created after August 26, 2026, files larger than 1 GB are not saved when the notebook shuts down.

marimo cloud — custom pricing. The closed beta offers on-demand cloud resources for experimentation, collaboration, sharing, and deployment. It is aimed at users seeking a managed cloud workflow rather than a local setup or the public-by-default molab option.

Platforms

marimo supports Linux, macOS, and Windows, as well as web and self-hosted use. API and editor-extension options broaden how developers can integrate it into their work. Supported notebook formats include Python (.py), Jupyter Notebook (.ipynb), HTML, PDF, and Markdown; supported languages are Python and SQL.

Who it's for

AI engineers, analysts, educators, analytics engineers, data engineers, data scientists, ML engineers, and web developers are the clearest audiences. It is best for people who want a Python notebook that can move into version control, scripts, or an interactive app. Those who need private hosted notebooks by default should look beyond molab.

Pros and cons

Pro: Reactive execution and deterministic behavior help keep code and outputs in sync, reducing a common source of notebook confusion.

Pro: Pure Python files work naturally with Git and can be run or reused outside the editor.

Pro: Interactive controls, SQL integrations, and multiple deployment paths support both exploration and sharing.

Con: Python is the center of the product, so teams focused on another language will be better served elsewhere.

Con: molab notebooks are public by default, and sessions are capped at 12 hours.

Con: Notebook execution can run arbitrary code; users must assess trust rather than treat the editor’s loading behavior as a security guarantee.

Alternatives

Deepnote is worth considering for teams wanting a hosted notebook option with a free plan that allows up to 3 editors and 5 projects.

Datalore may suit users who prefer a cloud plan with stated CPU-hour, storage, parallel-notebook, and workspace limits.

Paperspace Notebooks is an alternative for users seeking a free tier that includes CPU and GPU machines, with private-workspace and auto-shutdown limits.

Apache Zeppelin is a free, Apache-licensed open-source notebook option.

Hex offers a free Community plan with small compute and a Professional plan at $36 a month, billed per editor.

Nextjournal is an option for users prioritizing unlimited private notebooks on a free plan, with limited concurrent compute resources.

Pluto.jl is a free, MIT-licensed notebook option for work centered on Julia.

SageMath is a free open-source choice for users who want software they can install on unlimited computers and redistribute.

Browse more options in Notebook Software or Coding Playgrounds.

Verdict

Choose marimo if Python is your notebook language and you want reactive execution, Git-compatible files, and a route from analysis to interactive apps without paying for the open-source software. Look elsewhere if you need a different language or private hosted notebooks by default: molab’s public notebooks and bounded sessions are substantial trade-offs.