Platform	License	Ease of setup	Native integrations	Collaboration	Comments	Versioning	Reproducibility	Notebooks as products
Husprey	Proprietary	Fully managed	Data stores	Asynchrounous	Yes	Native	OK (only SQL)	Scheduled runs, public notebooks
Jupyter	Open Source	Local (easy) or on a server (hard)	N/A	Using git	No	Using git	Problematic	Plugins & python packages
Amazon SageMaker	Proprietary	Fully managed (but hard)	Within AWS	Shared copies	No	Using git	Problematic	No
Google Colab	Proprietary	Fully managed	Google Drive	Shared copies	No	No	Problematic	Parametrized inputs
Deepnote	Proprietary	Fully managed	Many	Real-time	Yes	Native	Environment, reactivity	Interactive applications, scheduled runs, articles
Databricks Notebooks	Proprietary	Fully managed	Data ingest tools	Real-time	Yes	Native	Environment	Scheduled runs
CoCalc	Open Source	Fully managed + self-hosting	No	Real-time	No	Native	Environment	No
Hex	Proprietary	Fully managed	Data stores	Real-time	Yes	Native	Environment, reactivity	Interactive applications
Kaggle Notebooks	Proprietary	Fully managed	Kaggle Datasets	Shared copies	No	Native	Environment	Articles
Facebook Bento	Proprietary	N/A	Internal data stores	Asynchrounous	Unclear	Unclear	Unclear	Reports
Nextjournal	Proprietary	Fully managed	Secrets, buckets	Real-time	Yes	Native	Environment	Articles
Jetbrains Datalore	Proprietary	Fully managed	Secrets, S3	Real-time	Yes	No	Environment, reactivity	Articles
Observable	Proprietary	In the browser	No	Real-time and Asynchronous	Yes	Yes	Environment, reactivity	Interactive applications
VS Code	Open Source	Local	No	Using git	Using git, in PRs	Using git, has pretty diffing	Problematic	No
Mode Notebooks	Proprietary	Fully managed	Many	Asynchronous	No	Only on queries	Environment	Shared reports
Zepl	Proprietary	Fully managed	Many	Real-time	Yes	Native	Environment	Scheduled runs, shared reports
Polynote	Open Source	Local (hard) or on a server (hard)	No	Using git	No	Using git	Problematic	No
Zeppelin	Open Source	Local (hard) or on a server (hard)	No	Asynchronous (on server)	No	Using git	Problematic	No
Count	Proprietary	Fully managed	Data stores	Real-time	No	No	OK (only SQL)	Shared reports
nteract	Open Source	Local	No	Using git	No	Using git	Problematic	No
Pluto.jl	Open Source	Local	No	Using git	Using git, in PRs	Using git	Reactivity	No
Query.me	Proprietary	Fully managed	SQL databases	Asynchrounous	No	No	OK (only SQL)	Public notebooks, shared reports
Querybook	Open Source	Local (hard) or on a server (hard)	Rich plugin ecosystem	Real-time	No	No	OK (only SQL)	Scheduled runs

Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. There's a number of vendors offering Jupyter notebooks as a managed service.

Colab notebooks allow you to combine executable code and rich text in a single document, along with images, HTML, LaTeX and more.

A notebook is a web-based interface to a document that contains runnable code, visualizations, and narrative text.

The Data Workspace for Teams. Work with data in collaborative SQL and Python notebooks. Share as interactive data apps that anyone can use.

Facebook Bento

An internal Facebook tool, presented at JupyterCon 2020.

A powerful online environment for Jupyter notebooks. Use smart coding assistance for Python in online Jupyter notebooks, run code on powerful CPUs and GPUs, collaborate in real-time, and easily share the results.

Visual Studio Code is a lightweight but powerful source code editor. It supports working with Jupyter Notebooks natively, as well as through Python code files.

Notebook-powered analytics for enterprise teams.

Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.

nteract is an open-source organization committed to creating fantastic interactive computing experiences that allow people to collaborate with ease.

Collaborative SQL Notebooks. A better way for data teams to analyze, unite & deliver.

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.

Deepnote is a new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud. Oh, and it's free.

Your best choice for teaching remote scientific courses!

Explore and run machine learning code with Kaggle Notebooks, a cloud computational environment that enables reproducible and collaborative analysis.

Runs anything you can put into a Docker container. Improve your workflow with polyglot notebooks, automatic versioning and real-time collaboration. Save time and money with on-demand provisioning, including GPU support.

Make sense of the world with data, together. Explore, visualize, and analyze data. Collaborate with the community. Learn and be inspired. Share insights with the world.

Native R & Python Notebooks. From SQL, explore your analysis using R or Python Notebooks.

Polynote is a different kind of notebook. It supports mixing multiple languages in one notebook, and sharing data between them seamlessly. It encourages reproducible notebooks with its immutable data model.

The BI notebook built for analysts. Simplify your workflow, collaborate with others and create the analysis your company craves in record time.

Writing a notebook is not just about writing the final document — Pluto empowers the experiments and discoveries that are essential to getting there.

Discover, analyze, and collaborate. Querybook is Pinterest’s open-source big data IDE via a notebook interface.

Alternatives to Husprey

Jupyter

Google Colab

Databricks Notebooks

Hex

Facebook Bento

Jetbrains Datalore

VS Code

Zepl

Zeppelin

nteract

Query.me

Amazon SageMaker

Deepnote

CoCalc

Kaggle Notebooks

Nextjournal

Observable

Mode Notebooks

Polynote

Count

Pluto.jl

Querybook

datasciencenotebook.org