Where data teams do their best work
Deepnote is a new kind of data science notebook. Jupyter compatible with real-time collaboration and runs in the cloud.
Deepnote is completely free. Get started in 10 seconds.
The world’s best data teams use Deepnote
Move faster with collaboration
We built Deepnote because analysts and data scientists don’t work alone.
Click on a link to jump into any project and see in real-time what everyone is up to.
No more out-of-sync files.
“Working in Deepnote is like code-review and rapid prototyping at the same time, saving valuable time in the iteration cycles.”
Luca Naef
CTO at VantAI
Share with your team, your clients, or the world
No need to email files or take screenshots of charts. In Deepnote, you can share projects by sending a link to anyone. By setting workspace permissions, you decide who can edit code and who can view it.
Review work in the right context
Discuss and debug in real-time by commenting on code and visualizations. No more email or Slack messages to get feedback on your work.
See history, track changes
Are you looking at the latest version of your file? See all changes as they happen when you are working with colleagues or clients.
Making you more productive
Explore all our features →We created Deepnote to help you save time. Whether you work in a team or by yourself, Deepnote helps you clean your data, write complex queries, build predictive models, and ship beautiful apps.
From Python to SQL and back
Don’t jump between multiple apps. Query data from wherever it’s stored, including Snowflake, BigQuery, Redshift and PostgreSQL. Switch between SQL and Python in order to transform, clean, and export your data.
Visualize data in seconds
Rapidly generate interactive charts to discover patterns in your data. No need to fuss with visualization libraries. Simply pick the data you want to plot, and Deepnote will do the rest.
Reproducible results
No more broken pip installs or mismatched requirements. Ensure reproducibility across your workspace by re-using the same environments throughout your projects. Create custom environments within Deepnote or import existing ones from Dockerhub, GCR, and ECR.
Write faster with autocomplete
Develop faster with intelligent autocomplete and linting tools. Deepnote points out bugs before they break long training jobs, just like you are used to from a local IDE such as VSCode, PyCharm or Sublime Text. The table names and columns are auto-suggested when writing SQL.
Integrates with everything
Deepnote integrates flawlessly with all your existing infrastructure and processes.
Use Python, R, Julia, TensorFlow, PyTorch, or any of your favorite languages or frameworks.
We’ve also pre-built 100s of native integrations that simplify the process of connecting your data sources.
All integrations are encrypted and can be easily shared with your workspace. No exposed passwords in your notebooks.
GitHub
Attach a repository to your project to read or commit to any branch.
Google Drive
Mount Google Drive directories in your projects to read and edit its files.
BigQuery
Connect to your BigQuery warehouse and query the data using Deepnote SQL blocks.
Snowflake
Connect to a Snowflake warehouse and query the data using Deepnote SQL blocks.
Amazon S3
Attach a bucket to your project and read, edit or upload files to the bucket.
PostgreSQL
Connect to a Postgres instance and use SQL directly from a notebook interface.
Enterprise-grade security
Secure by default, Deepnote has SOC 2 and follows industry best practices, including fine-grained access controls, SSO support and on-premise deployments.
Community
Deepnote is the favorite tool for thousands of data scientists all over the world.
Showcase your projects, join the discussion on best data science practices, or simply learn faster thanks to our community.
Thousands of members
Our community forums are the best place to get started and get answers to your Deepnote and data science questions.
The best place to learn
Whether it’s machine learning, visualizations, working with pandas or posting memes, we've got you covered.
Build Deepnote with us
Your feedback is what ultimately shapes Deepnote. Our community is the best place to give us feedback on new features you would like to see.
Loved by data scientists and analysts
Awesome service for working on Jupyter Notebooks collaboratively. My students are currently using it for their machine learning class projects; and it's also useful for me to check & comment. Really cool is the data management. No mounting required, it's just drag and drop.
Sebastian Raschka
Assistant Prof. of Statistics at @UWMadison@DeepnoteHQ Amazing tool. Have been using for just couple of days. Feels great to just start working rather than cracking my head on getting packages installed.
Darshan Ramesh
Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently.
Mike Xie
Data Scientist, Team Lead at Lambda SchoolVery impressed with the new @DeepnoteHQ! Managing SQL in a notebook's a nightmare! So the fact that you can now combine SQL cells with Python code is just SO neat! + connect direclty to Postgres, S3 or BigQuery.
Charly Wargnier
Py Dev | BI & SEO ConsultantGot early access to @DeepnoteHQ.This stuff is insane! Super intuitive and amazing UX. It's like a collaborative VSCode + Jupyter + Colab.
Ishaan Malhi
Machine Learning Engineer at Apple@DeepnoteHQ is amazing. You name the feature, it has all covered. Great UI, real-time collaboration, variable explorer, keyboard shortcuts, and many more make it a perfect Jupyter environment for the data scientist.
Shubham Agarwal
Machine learning is a very empirical discipline so iteration speed is everything - working in Deepnote is like code-review and rapid prototyping at the same time, saving valuable time in the iteration cycles.
Luca Naef
CTO at VantAIWorking on @ca_covid and trying out @DeepnoteHQ 1.5 years after a demo that was impressive even then and... wow. A bit blown away tbh.
Alec Wilson
Data Scientist at Vaccinate CA@DeepnoteHQ sealed the deal with real-time collaboration and fast boot times. I rarely find myself editing notebooks on my local machine anymore.
Adithya Balaji
Carnegie Mellon CS Masters StudentGet started with Deepnote today
Deepnote is a new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud.