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

Noteable vs Observable

Comparing two data science notebooks.

Noteable

Observable

A screenshot of Noteable

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

WebsiteAlternatives
A screenshot of Observable

Make sense of the world with data, together. Explore, visualize, and analyze data. Collaborate with the community. Learn and be inspired. Share insights with the world.

Setup

Is it managed?

Fully managed (setup in minutes)

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)
SQL

Programming languages

JS

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 sources can you connect to?

Connect with JS libraries (e.g. REST APIs)
Connect to databases (MySQL, Postgres)
Connect to data warehouses (BigQuery, Snowflake)
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?

JS data visualization (e.g. D3, Vega)

Reactivity

No reactivity, you decide the execution order

Reactivity

Full, realtime reactivity

Notebook scheduling

Notebook scheduling is built in
Notebook scheduling with additional tools

Notebook scheduling

No notebook scheduling

Management

Reproducibility

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

Reproducibility

Environments are reproducible by default
Execution is 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
Comment on a notebook as a whole

Comments

Comment on items within a notebook

Notebook organization

File-based

Notebook organization

View notebooks in a list

Licensing

License

Proprietary

License

Proprietary

Price

Free tier
Pay-per-user
Pay for compute

Price

Free tier
Free trial (1 month)
Pay-per-user

Alternatives to Noteable and Observable

Compare Noteable and Observable with other data science notebook tools.

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Noteable
Self-hosted or fully managedJupyter-compatibleJupyter, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
Observable
Fully managedNoneJSVisualize with codeRealtime collaborationFree and paid optionsProprietary
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