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 Noteable

Comparing two data science notebooks.

JupyterLab

Noteable

A screenshot of JupyterLab

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

WebsiteAlternatives
A screenshot of Noteable

Noteable is a collaborative notebook platform that enables teams to use and visualize data, together.

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?

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)

Programming languages

Jupyter languages (e.g. Python, R)
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 with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
Connect to databases (Trino, Snowflake, CockroachDB, PostgreSQL)
Connect to data warehouses (Amazon Redshift, Google BigQuery, Databricks)
Provided file storage

What kind of data visualization can you do?

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

What kind of data visualization can you do?

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

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

Notebook scheduling is built in
Notebook scheduling with additional tools

Management

Reproducibility

With effort, you can make reproducible environments

Reproducibility

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

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
Comment on a notebook as a whole

Notebook organization

File-based

Notebook organization

File-based

Licensing

License

Open-source (BSD)

License

Proprietary

Price

Free

Price

Free tier
Pay-per-user
Pay for compute

Alternatives to JupyterLab and Noteable

Compare JupyterLab and Noteable with other data science notebook tools.

ToolSetupJupyter compatibilityProgramming languagesData visualizationCollaborative editingPricingLicense
JupyterLab
Self-hostedJupyter-compatibleJupyterVisualize with codeFile-based or asynchronous collaborationFreeOpen source
Noteable
Self-hosted or fully managedJupyter-compatibleJupyter, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
Jupyter
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Data Science Notebooks

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