Hyperquery vs Jupyter: a side-by-side comparison for 2024
Comparing two data science notebooks.
Hyperquery
Hyperquery is a data notebook that enables you to easily build shareable analyses in SQL and Python.
Jupyter
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. There's a number of vendors offering Jupyter notebooks as a managed service.
Hyperquery
Jupyter
Setup
Is it managed?
Is it managed?
Fully managed (setup in minutes)
No, you must host it yourself
Can you self-host?
Can you self-host?
No, you must use a managed offering
You can self-host (setup in hours)
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)
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
With effort, you can make reproducible environments