Anaconda Individual Edition¶
Anaconda Individual Edition is a free, easy-to-install package manager, environment manager, and Python distribution with a collection of 1,500+ open source packages with free community support. Anaconda is platform-agnostic, so you can use it whether you are on Windows, macOS, or Linux.
The Anaconda Embedded Program allows you to power your products and services with with the world’s most popular open-source package distribution.
Anaconda Embedded enables you, as a product or service provider, to offer a seamless Python interface for your customers or use Anaconda behind the scenes to power your offering. All Embedded partners receive access to Anaconda’s premium repository, experts, and developers, as well as additional benefits like SLAs, co-marketing, and custom development opportunities.
Look for the “Powered By Anaconda” logo to identify products and services that are backed by Anaconda’s packages and software.
Learn more about Anaconda Embedded and contact a representative from the Anaconda Embedded product page.
Anaconda Commercial Edition¶
Anaconda Commercial Edition is the world’s most popular open-source package distribution and management experience, optimized for commercial use and compliance with our Terms of Service.
Anaconda Team Edition¶
Anaconda Team Edition is our latest generation repository for all things Anaconda. With support for all major operating systems, the repository serves as your central conda, PyPI, and CRAN packaging resource for desktop users, development clusters, CI/CD systems, and production containers.
Anaconda Enterprise Edition¶
Anaconda Enterprise is an enterprise-ready, secure, and scalable data science platform that empowers teams to govern data science assets, collaborate, and deploy data science projects.
Enterprise 5 includes these capabilities:
- Easily deploy your projects into interactive data applications, live notebooks, and machine learning models with APIs.
- Share those applications with colleagues and collaborators.
- Manage your data science assets: notebooks, packages, environments, and projects in an integrated data science experience.