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

Hyperquery vs Nextjournal

Comparing two data science notebooks.

Hyperquery

Nextjournal

A screenshot of Hyperquery

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

WebsiteAlternatives
A screenshot of Nextjournal

Runs anything you can put into a Docker container. Improve your workflow with polyglot notebooks, automatic versioning and real-time collaboration. Save time and money with on-demand provisioning, including GPU support.

Setup

Is it managed?

Fully managed (setup in minutes)

Is it managed?

Fully managed (setup in minutes)

Can you self-host?

No, you must use a managed offering

Can you self-host?

No, you must use a managed offering

Features

Is it Jupyter compatible?

Not Jupyter-compatible

Is it Jupyter compatible?

Jupyter-compatible

Programming languages

Python
SQL

Programming languages

Jupyter languages (e.g. Python, R)

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 sources can you connect to?

Connect with Jupyter libraries (e.g. SQLAlchemy, psycopg2)
Connect to data warehouses (AWS S3, Google Cloud Storage, etc.)
Connect to databases (SQLite, PostgreSQL, etc.)

What kind of data visualization can you do?

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

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

No notebook scheduling

Notebook scheduling

Notebook scheduling is built in

Management

Reproducibility

Environments are reproducible by default

Reproducibility

Environments are reproducible by default
Run notebooks in containers

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

Comments

Comment on items within a notebook

Notebook organization

View notebooks in a tree, like a wiki

Notebook organization

View notebooks in a list

Licensing

License

Proprietary

License

Proprietary

Price

Free tier
Pay-per-user

Price

Free tier
Pay-per-user
Pay for compute

Alternatives to Hyperquery and Nextjournal

Compare Hyperquery and Nextjournal with other data science notebook tools.

ToolSetupJupyter compatibilityProgramming languagesData visualizationCollaborative editingPricingLicense
Hyperquery
Fully managedNonePython, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary
Nextjournal
Fully managedJupyter-compatibleJupyterVisualize with codeRealtime collaborationFree and paid optionsProprietary
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