Use SQL to query Snowflake from a notebook
Don’t jump between multiple apps. Query data directly from your Snowflake data warehouse. Switch between SQL and Python in order to transform, clean, and export your data.
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Snowflake in Jupyter notebooks
Snowflake is an enterprise-ready data warehouse that lets you separate your compute from storage.
When connected to a Deepnote notebook, you can read, update or delete any data directly with Snowflake SQL queries. The query result can be saved as a dataframe and later analyzed or transformed in Python, or plotted with Deepnote's visualization cells without writing any code.
Collaborative by default
We built collaboration into Deepnote by default because data teams don’t work alone.
Deepnote runs seamlessly in the cloud, making environment management a non-issue. And sharing work is as easy as sending a link (think Google Docs).
Allie Russell · Senior Manager, Data Science at Webflow
“Deepnote allowed us get on the same page through collaboration, and everyone gets to use their preferred tools.”
Integrates with your data stack
Deepnote works with the tools and frameworks you’re already using and familiar with. Use Python, SQL, R, TensorFlow, PyTorch, and any of your favorite languages or frameworks. Easily connect to data sources with dozens of native integrations.
Becca Carter · Analytics Lead at Gusto
”Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds.”
