View all notebooks

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.

Amazon Sagemaker vs Zepl

Comparing two data science notebooks.

Amazon Sagemaker

Zepl

A screenshot of Amazon Sagemaker

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.

WebsiteAlternatives
A screenshot of Zepl

Notebook-powered analytics for enterprise teams.

Setup

Is it managed?

Fully managed (setup in hours)

Is it managed?

Fully managed (setup in hours)

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?

Jupyter-compatible

Is it Jupyter compatible?

Unknown

Programming languages

Jupyter languages (e.g. Python, R)

Programming languages

Python
R

What kind of data sources can you connect to?

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

What kind of data sources can you connect to?

Unknown

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

Unknown

Notebook scheduling

Notebook scheduling with additional tools

Notebook scheduling

Notebook scheduling is built in

Management

Reproducability

There is no support for reproducability

Reproducability

Environments are reproducible by default

Version history

File-based (use Git)

Version history

Version history is built in

Collaborative editing

No support for collaborative editors

Collaborative editing

Multiple editors at the same time

Comments

File-based (use GitHub)

Comments

Comment on items within a notebook

Notebook organization

View notebooks in a list

Notebook organization

Unknown

Licensing

License

Proprietary

License

Proprietary

Price

Free tier
Pay for compute

Price

Unknown

Alternatives to Amazon Sagemaker and Zepl

Compare Amazon Sagemaker and Zepl with other data science notebook tools.

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Amazon Sagemaker
Fully managedJupyter-compatibleJupyterVisualize with codeLimited collaborationFree and paid optionsProprietary
Zepl
Fully managedUnknownPython, RUnknownRealtime collaborationUnknownProprietary
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