View all notebooks

Data Science Notebooks

Data science gets done in notebooks. This website exists to compare the features in different data science notebook tools.

Robert Lacok
About the author

My name is Robert Lacok, and I’m a data notebook enthusiast. Because I keep on top of the latest developments in the space, I wanted to share it with the world.

I’m also a product manager at Deepnote. I try to be unbiased — if you believe any tools are missing or misrepresented, please email me or open a pull request on GitHub.

Need help?

If you need help picking a data notebook for your next project, feel free to reach out to me at my personal email address. I’d be happy to chat about the pros and cons of each solution.

Hex vs CoCalc

Comparing two data science notebooks.

Hex

CoCalc

A screenshot of Hex

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

WebsiteAlternatives
A screenshot of CoCalc

Your best choice for teaching remote scientific courses.

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Setup

Is it managed?

Fully managed (setup in minutes)

Is it managed?

Fully managed (setup in minutes)

Can you self-host?

No, you must use a managed offering

Can you self-host?

You can self-host (setup in hours)

Features

Is it Jupyter compatible?

Jupyter-compatible

Is it Jupyter compatible?

Jupyter-compatible

Programming languages

Jupyter languages (e.g. Python, R)
SQL

Programming languages

Jupyter languages (e.g. Python, R)

What kind of data sources can you connect to?

Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
Connect to data warehouses (Google BigQuery, ClickHouse, etc.)
Connect to databases (MariaDB, SQL Server, etc.)
Provided file storage

What kind of data sources can you connect to?

Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
Provided file storage

What kind of data visualization can you do?

Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)
UI for building charts

What kind of data visualization can you do?

Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)

Reactivity

Full, realtime reactivity

Reactivity

No reactivity, you decide the execution order

Notebook scheduling

Notebook scheduling is built in

Notebook scheduling

No notebook scheduling

Management

Reproducability

Environments are reproducible by default
Execution is reproducible by default
Run notebooks in containers

Reproducability

Environments are reproducible by default

Version history

Version history is built in

Version history

Version history is built in

Collaborative editing

Multiple editors at the same time

Collaborative editing

Multiple editors at the same time

Comments

Comment on items within a notebook

Comments

No support for comments

Notebook organization

View notebooks in a list

Notebook organization

View notebooks in a list

Licensing

License

Proprietary

License

Open-source (GNU AGPLv3)

Price

Free tier
Pay-per-user
Pay for compute

Price

Free tier
Pay for compute

Alternatives to Hex and CoCalc

Compare Hex and CoCalc with other data science notebook tools.

ToolSetupJupyter compatibilityProgramming languagesData visualizationCollaborative editingPricingLicense
Hex		Fully managedJupyter-compatibleJupyter, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
CoCalc		Self-hosted or fully managedJupyter-compatibleJupyterVisualize with codeRealtime collaborationFree and paid optionsOpen source
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