Deepnote

Deepnote

Freemium

Collaborative data science notebook that combines Python, SQL, and AI assistance for teams to explore and share data insights together.

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What is Deepnote?

Deepnote is a cloud-based, collaborative data science notebook platform designed for teams to explore data, build analyses, and share insights without local environment setup. It supports Python and SQL in the same notebook, features an AI code copilot for instant suggestions, and provides no-code data visualization blocks for turning DataFrames into charts in seconds. Deepnote runs in a fully managed cloud environment with GPU support for ML workloads, and offers real-time multiplayer editing similar to Google Docs. It integrates with all major data warehouses and supports ETL pipelines, dbt, Spark, and Snowpark for data engineering workflows. The platform is now open-source, making it popular with academic and data engineering communities.

Key Features

AI Code CopilotReal-Time Multiplayer EditingPython and SQL SupportNo-Code Data VisualizationGPU Hardware SupportETL Pipeline Builderdbt IntegrationSpark and Snowpark SupportCode Review WorkflowsVersion HistoryDocker Environment SupportScheduled NotebooksData Catalog IntegrationSOC 2 and HIPAA CompliantOne-Click Sharing

How to Use Deepnote

1Sign up and create a Deepnote project (no local setup required)
2Connect your data source (BigQuery, Snowflake, PostgreSQL, and more)
3Write Python or SQL in notebook cells with AI code suggestions
4Use no-code visualization blocks to chart your DataFrames
5Share via link or publish as a data app for stakeholders

✅ Best For

  • Data science teams and ML engineers who need a collaborative, cloud-based notebook environment with GPU access and ETL capabilities, without the overhead of managing local Jupyter setups.
  • Academic researchers, students, and bootcamp graduates who want a free, fully managed Python and SQL environment with easy sharing and version control built in.

❌ Not For

  • Business users who need a no-code, point-and-click dashboard builder without any exposure to Python or SQL code, as Deepnote's core workflow is notebook-based.
  • Enterprise teams requiring an all-in-one BI platform with drag-and-drop report builders and business-user-friendly self-serve features out of the box.

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Pricing

Free$0
  • ✓1 workspace
  • ✓5 projects
  • ✓750 compute hours/month
Team$39/user/mo
  • ✓Unlimited projects
  • ✓advanced compute
  • ✓SSO
EnterpriseCustom
  • ✓Private deployment
  • ✓HIPAA
  • ✓audit logs
  • ✓dedicated support

Prompts to Try

Write a Python script to merge two DataFrames and calculate monthly revenue by product

Run a SQL query on my BigQuery table and plot the result as a line chart

Clean this dataset by removing nulls and standardizing column names

Train a simple linear regression model on this sales data

Schedule this notebook to run every Monday at 9am and email me the output

Use Cases

A data scientist at a biotech startup uses Deepnote's GPU environment to train a customer churn prediction model and shares the results notebook with the product team via a single link, replacing a 20-slide PowerPoint.
A fintech analytics team uses real-time multiplayer editing in Deepnote to collaboratively build a fraud detection pipeline during a 2-hour working session, with three analysts editing simultaneously.
A data engineering lead sets up an ETL notebook in Deepnote that pulls from Snowflake, cleans the data with Python, and schedules it to run nightly, replacing a fragile cron job.
A university professor shares a Deepnote notebook with 60 students for a machine learning assignment, and every student gets an identical cloud environment without any local installation issues.
A growth analyst uses Deepnote's SQL blocks and no-code charts to quickly prototype a user cohort analysis dashboard, then hands it off to the engineering team to productionize.

Frequently Asked Questions