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Hyperquery vs Amazon Sagemaker:
a side-by-side comparison for 2024

Comparing two data science notebooks.

A screenshot of Hyperquery
Hyperquery logo

Hyperquery

Website
Hyperquery is a data notebook that enables you to easily build shareable analyses in SQL and Python.
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A screenshot of Amazon Sagemaker
Amazon Sagemaker logo

Amazon Sagemaker

Website
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.

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Hyperquery

Amazon Sagemaker

Setup

Is it managed?

Is it managed?

Fully managed (setup in minutes)
Fully managed (setup in hours)

Can you self-host?

Can you self-host?

No, you must use a managed offering
No, you must use a managed offering

Features

Is it Jupyter compatible?

Is it Jupyter compatible?

Not Jupyter-compatible
Jupyter-compatible

Programming languages

Programming languages

Python
SQL
Jupyter languages (e.g. Python, R)

What kind of data sources can you connect to?

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

What kind of data visualization can you do?

What kind of data visualization can you do?

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

Reactivity

Reactivity

No reactivity, you decide the execution order
No reactivity, you decide the execution order

Notebook scheduling

Notebook scheduling

No notebook scheduling
Notebook scheduling with additional tools

Management

Reproducibility

Reproducibility

Environments are reproducible by default
There is no support for reproducibility

Version history

Version history

Version history is built in
File-based (use Git)

Collaborative editing

Collaborative editing

Multiple editors at the same time
No support for collaborative editors

Comments

Comments

Comment on items within a notebook
File-based (use GitHub)

Notebook organization

Notebook organization

View notebooks in a tree, like a wiki
View notebooks in a list

Licensing

License

License

Proprietary
Proprietary

Price

Price

Free tier
Pay-per-user
Free tier
Pay for compute

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Alternatives to Hyperquery and Amazon Sagemaker

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

ToolSetupJupyter compatibilityLanguagesData visualizationCollaborative editingPricingLicense

Hyperquery

Fully managedNonePython, SQLVisualize with code or UIRealtime collaborationFree and paid optionsProprietary

Amazon Sagemaker

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