Count
WebsiteCount helps your data team work closer with the business so everyone is working on the problems that matter. Fast.
Count vs Hyperquery:
a side-by-side comparison for 2024
Comparing two data science notebooks.
Hyperquery
WebsiteHyperquery is a data notebook that enables you to easily build shareable analyses in SQL and Python.
Count
Hyperquery
Setup
Is it managed?
Is it managed?
Fully managed (setup in minutes)
Fully managed (setup in minutes)
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
Not Jupyter-compatible
Programming languages
Programming languages
SQL
Python
SQL
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, MongoDB, etc.)
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 visualization can you do?
What kind of data visualization can you do?
UI for building charts
UI for building charts
Jupyter data visualization (e.g. Matplotlib, Altair, Plotly)
Reactivity
Reactivity
Unknown
No reactivity, you decide the execution order
Notebook scheduling
Notebook scheduling
No notebook scheduling
No notebook scheduling
Management
Reproducibility
Reproducibility
Unknown
Environments are reproducible by default
Version history
Version history
Version history is built in
Version history is built in
Collaborative editing
Collaborative editing
Multiple editors at the same time
Multiple editors at the same time
Comments
Comments
Comment on items within a notebook
Comment on items within a notebook
Notebook organization
Notebook organization
View notebooks in a list
View notebooks in a tree, like a wiki
Licensing
License
License
Proprietary
Proprietary
Price
Price
Free tier
Pay-per-user
Free tier
Pay-per-user