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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.

VS Code vs Zeppelin

Comparing two data science notebooks.

VS Code

Zeppelin

A screenshot of VS Code

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.

WebsiteAlternatives
A screenshot of Zeppelin

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

WebsiteAlternatives

Setup

Is it managed?

No, you must host it yourself

Is it managed?

No, you must host it yourself

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?

Not Jupyter-compatible

Programming languages

Jupyter languages (e.g. Python, R)

Programming languages

Python
SQL
Spark

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?

What kind of data visualization can you do?

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

What kind of data visualization can you do?

Unknown

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

Management

Reproducability

There is no support for reproducability

Reproducability

With effort, you can make reproducible environments

Version history

File-based (use Git)

Version history

File-based (use Git)

Collaborative editing

File-based (use Git)

Collaborative editing

File-based (use Git)
Multiple editors, one at a time (asynchronous)

Comments

File-based (use GitHub)

Comments

File-based (use GitHub)

Notebook organization

File-based

Notebook organization

File-based

Licensing

License

Open-source (MIT)

License

Open-source (Apache 2.0)

Price

Free

Price

Free

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VS Code		Self-hostedJupyter-compatibleJupyterVisualize with codeFile-based or asynchronous collaborationFreeOpen source
Zeppelin		Self-hostedNonePython, SQL, SparkUnknownFile-based or asynchronous collaborationFreeOpen source
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