Quick comparison # App Pricing Verified price Open source Platforms Verified facts Score 1 Google ColabFree plan + paid — No Web 4 of 4 68.8 2 HexFree plan + paid $36 per editor/month (Professional) No Web 5 of 5 59.4 3 marimoOpen source — Yes Windows, macOS, Linux +2 4 of 4 57.5 4 Jupyter NotebookOpen source — Yes Web, Windows, macOS +2 5 of 5 54.4 5 DataCampFree plan + paid — No Web, iOS, Android 5 of 5 46.8
1 Best for: Students and ML learners who want free GPU notebooks with nothing to install
Free plan + paid Web
Why switch from Kaggle
Also free hosted notebooks with GPU access, but tied to Google Drive and better for private work.
Pros Free access to GPUs and TPUs for learning and small experiments No setup: runs entirely in the browser with a Google account Standard .ipynb files that open in any Jupyter toolCons Free resources are not guaranteed and sessions get terminated Data has to be uploaded or mounted from Google Drive each session Real-time collaboration is weaker than in team notebook toolsHow this score is calculated Editorial fit ×0.3 100
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
Verified facts 4 of 4 verified 2 Best for: Analytics teams on a cloud warehouse who want notebooks that become shareable data apps
Free plan + paid Web
Why switch from Kaggle
Notebook-style analytics for teams, with SQL, Python and shareable data apps.
Pros Notebooks publish as interactive apps for non-technical colleagues Works with dbt, Airflow and Dagster Free trial of the Team plan needs no payment cardCons Community plan is limited to small compute and light AI use Per-editor pricing is high compared with general notebook tools Larger machines and GPUs are billed per minute on top of the planHow this score is calculated Editorial fit ×0.3 69
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
3 Best for: Python developers who want reproducible notebooks that live in Git as normal code
Open source Self-hostable Windows, macOS, Linux, Web, Self-hosted
Why switch from Kaggle
Open-source reactive Python notebooks stored as plain .py files, runnable locally or in a free web sandbox.
Pros Reactive execution removes stale or out-of-order state Notebooks are plain .py files with readable Git diffs Can run as a script or be served as an interactive app Free and Apache-2.0 licensedCons Not compatible with Jupyter's .ipynb format without conversion Python only, with no R or Julia kernels Reactive model means reusing a variable name across cells is not allowedHow this score is calculated Editorial fit ×0.3 63
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
4 Best for: Students, researchers and data analysts who want to explore data step by step in a shareable document
Open source Self-hostable Web, Windows, macOS, Linux, Self-hosted
Why switch from Kaggle
Run the same notebook workflow on your own machine or server with no session limits.
Pros Free and open source with no paid tier Supports many languages through separate kernels Notebooks render on GitHub and are easy to share Can be run for a whole class or team with JupyterHubCons Needs a local Python setup or a server; no official desktop installer Out-of-order cell execution makes results easy to break Old v6 extensions don't work in Notebook 7 Weak fit for large codebases, refactoring and debuggingHow this score is calculated Editorial fit ×0.3 52
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
Verified facts 5 of 5 verified License BSD-3-Clause Checked Nov 1, 2026github.com(opens source in a new tab) Languages 40+, incl. Python, R, Julia Checked Nov 8, 2026jupyter.org(opens source in a new tab) Install pip install notebook Checked Nov 8, 2026jupyter.org(opens source in a new tab) Origin IPython project, 2014 Checked Nov 8, 2026jupyter.org(opens source in a new tab) Notebook format Open, JSON-based Checked Nov 8, 2026jupyter.org(opens source in a new tab) 5 Best for: Analysts and beginners who want hands-on Python, SQL and AI practice without setting anything up
Free plan + paid Web, iOS, Android
Why switch from Kaggle
Structured data science courses with a hosted notebook workspace, if you used Kaggle Learn to study.
Pros Write and run code in the browser from the first lesson Large catalogue of data, AI and BI courses in tracks Recognised data analyst and data scientist certificationsCons Free plan only opens the first lesson of each course Exercises are short and guided, so deeper projects need work elsewhere Narrow focus on data and AI rather than general software developmentHow this score is calculated Editorial fit ×0.3 34
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 85
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula