Sign inGet started

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.

Get started – it’s freeRead the Google BigQuery docs

Loved by 100,000s of data professionals

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 in Jupyter notebooks docs →
Snowflake, MongoDB, PostgreSQL and an Amazon S3 bucket connected to a Deepnote project as integrations

Collaborate with the whole team

Deepnote runs seamlessly in the cloud, making environment management and collaboration with your team a non-issue. And sharing work is as easy as sending a link or email invite.

Product manager

Organize your work

Build a library of data projects sorted by folders so teammates can get needed information fast.

Comment, review, version

Have your team comment on blocks to ask questions, provide feedback, and work faster.

Data scientist

Sharing made simple

Share your work with others by simply sending a link or email invite. Or use advanced permission models.

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.

Browse integrations →

Datastores and Metrics

Languages

Libraries

Footer

Product

  • Integrations
  • Pricing
  • Documentation
  • Changelog
  • Security

Company

Comparisons

Resources

  • Privacy
  • Terms

© Deepnote