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Use BigQuery directly in a notebook

Don’t jump between multiple apps. Query data directly from your Google BigQuery warehouse. Switch between SQL and Python in order to transform, clean, and export your data.

Read the BigQuery docs
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An exploratory analysis in Deepnote notebook

BigQuery in Jupyter notebooks

BigQuery is an cloud-based data warehouse solution by Google.

When connected to a Deepnote notebook, you can read, update or delete any data directly with BigQuery 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.

Explore BigQuery docs →
Snowflake, MongoDB, PostgreSQL and an Amazon S3 bucket connected to a Deepnote project as integrations

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 Russel

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.”

Webflow
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Team of 4 collaborators with different permissions for greater data security

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

Becca Carter · Analytics Lead at Gusto

”Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds.”

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