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

Databricks Notebooks vs VS Code

Comparing two data science notebooks.

Databricks Notebooks

VS Code

A screenshot of Databricks Notebooks

Collaborate across engineering, data science, and machine learning teams with support for multiple languages, built-in data visualizations, automatic versioning, and operationalization with jobs.

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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.

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Setup

Is it managed?

Fully managed (setup in minutes)

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?

Jupyter-compatible

Programming languages

Jupyter languages (e.g. Python, R)

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 (Databricks)

What kind of data sources can you connect to?

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

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

No reactivity, you decide the execution order

Reactivity

No reactivity, you decide the execution order

Notebook scheduling

Notebook scheduling is built in

Notebook scheduling

Notebook scheduling with additional tools

Management

Reproducibility

Environments are reproducible by default

Reproducibility

There is no support for reproducibility

Version history

Version history is built in

Version history

File-based (use Git)

Collaborative editing

Multiple editors at the same time

Collaborative editing

File-based (use Git)

Comments

Comment on items within a notebook

Comments

File-based (use GitHub)

Notebook organization

View notebooks in a list

Notebook organization

File-based

Licensing

License

Proprietary

License

Open-source (MIT)

Price

Free tier
Pay for compute

Price

Free

Alternatives to Databricks Notebooks and VS Code

Compare Databricks Notebooks and VS Code with other data science notebook tools.

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Databricks Notebooks		Self-hosted or fully managedJupyter-compatibleJupyterVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
VS Code		Self-hostedJupyter-compatibleJupyterVisualize with codeFile-based or asynchronous collaborationFreeOpen source
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Data Science Notebooks

Popular notebook tools

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Popular notebook comparisons

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Notebook tools by feature

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