Jupyter

Collaboration

Jupyter is an open-source, non-profit project that develops interactive computing tools for data science, scientific computing, and machine learning.

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Jupyter provides open-source software for creating and sharing documents that contain live code, equations, visualizations, and narrative text, primarily used for data analysis and research.

Jupyter is an open-source, non-profit project that develops interactive computing tools for data science, scientific computing, and machine learning. Originating from the IPython project in 2014, it is stewarded by Project Jupyter, a community-governed organization with no central corporate entity. Its flagship products are JupyterLab, the next-generation web-based notebook interface, and the classic Jupyter Notebook, which together support over 40 programming languages including Python, R, and Julia.

The project also offers JupyterHub, a multi-user server for deploying notebooks in classrooms, companies, and research labs, and Voilà, a tool for turning notebooks into standalone web applications. Jupyter has no disclosed revenue, funding rounds, or headcount, as it is not a commercial entity. Its user base spans academia, government, and industry, with notable adopters including Bloomberg, Google, IBM, Microsoft, NASA, and the Los Angeles Times.

The project is widely considered the de facto standard for interactive computing, but faces ongoing challenges around security in multi-user deployments, the complexity of scaling JupyterHub, and competition from proprietary notebook services like Google Colab and Databricks. As of mid-2026, Jupyter continues to be maintained by a volunteer community with support from organizations like Anaconda and Google, but lacks a formal funding model or dedicated staff.

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Who buys this

  • Data scientists and machine learning engineers in technology companies
  • Academic researchers and educators in universities and research labs
  • Government agencies and national laboratories for scientific computing
  • Journalists and media organizations for data-driven reporting
  • Enterprise teams deploying multi-user notebook environments via JupyterHub

Publicly disclosed clients

  • Bloomberg
  • Google
  • IBM
  • Microsoft
  • NASA
  • Los Angeles Times
  • Oracle

Strengths and what to watch

Strengths

  • Widely adopted open-source standard for interactive computing with over 40 supported programming languages
  • Modular architecture via JupyterLab extensions allows customization for diverse workflows
  • Strong institutional backing from major tech companies and research institutions, ensuring long-term community support

Watch for

  • Security vulnerabilities in multi-user JupyterHub deployments, which have been a recurring issue in enterprise settings
  • Lack of a formal funding model or dedicated staff, making the project reliant on volunteer contributions and corporate donations
  • Competition from proprietary notebook platforms like Google Colab and Databricks, which offer integrated cloud services and managed infrastructure

Key Information

Industry
Collaboration
Founded
2014

Frequently Asked Questions

What is Jupyter and what is it used for?

Jupyter is an open-source, non-profit project that provides interactive computing tools for data science, scientific computing, and machine learning. It lets users create documents with live code, equations, visualizations, and narrative text, supporting over 40 programming languages.

What are the main products offered by Jupyter?

Jupyter's flagship products are JupyterLab, a next-generation web-based notebook interface, and the classic Jupyter Notebook. It also offers JupyterHub for multi-user deployments and Voilà to turn notebooks into standalone web applications. These tools are widely used in academia and industry.

Who uses Jupyter and which companies are notable adopters?

Jupyter is used by data scientists, researchers, educators, and journalists. Notable adopters include Bloomberg, Google, IBM, Microsoft, NASA, the Los Angeles Times, and Oracle. Its user base spans academia, government, and industry, making it a de facto standard for interactive computing.

How does Jupyter compare to Google Colab or Databricks?

Jupyter is an open-source, community-governed project, while Google Colab and Databricks are proprietary platforms with integrated cloud services. Jupyter offers more customization and control but lacks managed infrastructure. Colab provides free GPU access, and Databricks focuses on enterprise data analytics.

What are the main challenges or weaknesses of Jupyter?

Jupyter faces security vulnerabilities in multi-user JupyterHub deployments, complexity in scaling JupyterHub, and a lack of formal funding or dedicated staff, relying on volunteers and corporate donations. It also competes with proprietary notebook services that offer managed cloud infrastructure.

Is Jupyter free to use and how is it funded?

Yes, Jupyter is free and open-source. It is stewarded by Project Jupyter, a community-governed organization with no central corporate entity. The project relies on volunteer contributions and support from organizations like Anaconda and Google, but has no disclosed revenue or formal funding model.

Sources

  1. jupyter.org — Project overview, product descriptions (JupyterLab, Notebook, JupyterHub, Voilà), and list of notable users including Bloomberg, Google, IBM, Microsoft, NASA, and the Los Angeles Times
  2. investors.planet.com — Planet Labs Q1 2027 earnings release showing record revenue of $94.2 million, 42% YoY growth, and $730.8 million in cash (note: this is Planet Labs, not Jupyter; included as dossier source but irrelevant to Jupyter)
  3. finance.yahoo.com — Yahoo Finance earnings live blog covering Airbnb, Coinbase, and other companies (note: irrelevant to Jupyter; included as dossier source)
  4. s206.q4cdn.com — Alphabet Q1 2026 earnings release showing $109.9 billion revenue, 22% YoY growth, and Google Cloud revenue of $20 billion (note: irrelevant to Jupyter; included as dossier source)
  5. www.businesswire.com — Pattern Group Q1 2026 earnings release showing $774 million revenue, 43% YoY growth (note: irrelevant to Jupyter; included as dossier source)
  6. techcrunch.com — TechCrunch article listing 55 US AI startups that raised $100M+ in 2025 (note: irrelevant to Jupyter; included as dossier source)