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Head-to-head · Python Package Managers

uv vs Anaconda Distribution

  • Updated Oct 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score uv #1 in Python Package Managers 9.3/10 Free plan Free plan✓ 1 of 5 features Visit uv
Anaconda Distribution #7 in Python Package Managers 8.4/10 Free plan Free plan✓ 4 of 5 features Visit Anaconda

uv leads on 0 checks, Anaconda Distribution on 0, and 5 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreuv · 9.3/10
  • Free planboth
  • Most featuresAnaconda Distribution · 4 of 5

uv scores higher on our rubric for python package managers: 9.3 against 8.4 out of 10; our editors rank them #1 and #7.

uv is the better fit for modern all-in-one Python project management. Anaconda Distribution is the better fit for data science users wanting a managed distribution.

  • uv fits best

    Modern all-in-one Python project management

  • Anaconda Distribution fits best

    Data science users wanting a managed distribution

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Side by side

Feature uv 9.3/10 Visit ↗ Anaconda Distribution 8.4/10 Visit ↗
At a glance
Editor score 9.3 8.4
Ranking #1 in Python Package Managers #7 in Python Package Managers
Best for Modern all-in-one Python project management Data science users wanting a managed distribution
Pricing model Free Free plan + paid
Starting price Free plan $15/user/mo
Free plan ✓ ✓
Free trial — —
Deployment Desktop Desktop
Platforms Windows, macOS, Linux Windows, macOS, Linux
Support Docs Tickets, Community, Docs
Integrations 17 integrations 2 integrations
Built for Solo, Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features uv 1/5 · Anaconda Distribution 4/5
Lockfile support ✓ ✓
Environment management Not checked yet ✓ (best)
Package publishing Not checked yet ✓ (best)
Private registry Not checked yet ✓ (best)
Dependency groups Not checked yet Not checked yet
Specs
Supported platforms Not checked yet Cross-platform
Our review
Pros
  • Universal lockfiles support consistent resolution across macOS, Linux, and Windows
  • Combines environments, Python versions, workspaces, builds, and publishing
  • Supports private indexes, Git and local dependencies, caching, and offline operation
  • Conda manages isolated environments, packages, lockfiles, and channels.
  • Includes Python, Jupyter Notebook, JupyterLab, Navigator, and data science packages.
  • Runs on Windows, macOS, and Linux with desktop and command-line workflows.
Cons
  • Its broad scope may be more than users seeking only pip-compatible installation need
  • Cargo-style workspaces are useful mainly for multi-package repositories
  • Additional architectures and operating systems have separate support tiers
  • Paid tiers add recurring per-user monthly costs.
  • Its broad data science focus may exceed the needs of minimal Python setups.
  • Team governance and security controls start in higher-priced plans.
Our verdict

uv is an open-source Python package and project manager from Astral, written in Rust. It is aimed at individual developers and teams that want one tool for dependency resolution, project and virtual-environment management, Python version…

Read the review →

Anaconda Distribution bundles Python, Jupyter Notebook, JupyterLab, conda, Navigator, and a curated collection of data science, machine learning, and AI packages. It is designed for learners, individual developers, data scientists, and…

Read the review →
  1. uvPython Package Managers 9.3Free plan
  2. Anaconda DistributionPython Package Managers 8.4Free plan

Strengths and trade-offs

  • uv — where it wins

    • Universal lockfiles support consistent resolution across macOS, Linux, and Windows
    • Combines environments, Python versions, workspaces, builds, and publishing
    • Supports private indexes, Git and local dependencies, caching, and offline operation

    Where it doesn't

    • Its broad scope may be more than users seeking only pip-compatible installation need
    • Cargo-style workspaces are useful mainly for multi-package repositories
    • Additional architectures and operating systems have separate support tiers

  • Anaconda Distribution — where it wins

    • Conda manages isolated environments, packages, lockfiles, and channels.
    • Includes Python, Jupyter Notebook, JupyterLab, Navigator, and data science packages.
    • Runs on Windows, macOS, and Linux with desktop and command-line workflows.

    Where it doesn't

    • Paid tiers add recurring per-user monthly costs.
    • Its broad data science focus may exceed the needs of minimal Python setups.
    • Team governance and security controls start in higher-priced plans.
  • uv9.3/10 · Free plan

    An open-source toolkit for managing modern Python projects from dependencies to publishing.

    Visit uvFull verdict →
  • Anaconda Distribution8.4/10 · Free plan

    A broad Python and data science toolkit with free core package management.

    Visit AnacondaFull verdict →

More comparisons

All python package managers comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update