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.

View all notebooks

JupyterLab vs Hyperquery

Comparing two data science notebooks.

JupyterLab

Hyperquery

A screenshot of JupyterLab

JupyterLab is the next-generation web-based user interface for Project Jupyter.

WebsiteAlternatives
A screenshot of Hyperquery

Hyperquery is a data notebook that enables you to easily build shareable analyses in SQL and Python.

Setup

Is it managed?

No, you must host it yourself

Is it managed?

Fully managed (setup in minutes)

Can you self-host?

You can self-host (setup in hours)

Can you self-host?

No, you must use a managed offering

Features

Is it Jupyter compatible?

Jupyter-compatible

Is it Jupyter compatible?

Not Jupyter-compatible

Programming languages

Jupyter languages (e.g. Python, R)

Programming languages

Python
SQL

What kind of data sources can you connect to?

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

What kind of data sources can you connect to?

Connect to data warehouses (AWS, GCP, etc.)
Connect to databases (Postgres, MS SQL, etc.)
Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)

What kind of data visualization can you do?

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

What kind of data visualization can you do?

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

Reactivity

No reactivity, you decide the execution order

Reactivity

No reactivity, you decide the execution order

Notebook scheduling

Notebook scheduling with additional tools

Notebook scheduling

No notebook scheduling

Management

Reproducibility

With effort, you can make reproducible environments

Reproducibility

Environments are reproducible by default

Version history

File-based (use Git)

Version history

Version history is built in

Collaborative editing

File-based (use Git)
Experimental JupyterLab support

Collaborative editing

Multiple editors at the same time

Comments

File-based (use GitHub)

Comments

Comment on items within a notebook

Notebook organization

File-based

Notebook organization

View notebooks in a tree, like a wiki

Licensing

License

Open-source (BSD)

License

Proprietary

Price

Free

Price

Free tier
Pay-per-user

Alternatives to JupyterLab and Hyperquery

Compare JupyterLab and Hyperquery with other data science notebook tools.

ToolSetupJupyter compatibilityProgramming languagesData visualizationCollaborative editingPricingLicense
JupyterLab
Self-hostedJupyter-compatibleJupyterVisualize with codeFile-based or asynchronous collaborationFreeOpen source
Hyperquery
Fully managedNonePython, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
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