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Machine Learning · head to head

Anaconda vs DeepSource

Anaconda logo

Anaconda

Machine Learning

The world's most popular data science platform

From
Free
Rated
-
Full reviewWebsite
DeepSource logo

DeepSource

Software Development

Automated code review and AI-powered code fixes for engineering teams.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Anaconda dependency resolution slower than pip due to SAT solver complexity; DeepSource open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.
  • They diverge on capability: Anaconda covers Conda package manager, DeepSource covers Automated pull request review.

Where they differ

Only the attributes on which Anaconda and DeepSource actually diverge.

Attributes where Anaconda and DeepSource differ
AttributeAnacondaDeepSource
Pricing modelUnknownfreemium
PlatformsWindows, macOS, Linux, Web/Cloudweb, api
CategoryMachine LearningSoftware Development
Founded2012Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Anaconda

  • Conda package manager
  • Environment management
  • 1500+ packages
  • Navigator GUI
  • Cross-platform support
  • Jupyter
  • VS Code
  • PyCharm

Only in DeepSource

  • Automated pull request review
  • AI-powered autofix
  • Automated code formatting
  • Monorepo support
  • API and webhooks
  • Bring-your-own-key AI

What people use each for

The jobs each tool is most often brought in to do.

Anaconda

  • Machine learningnot DeepSource
  • Data analysisnot DeepSource
  • Model trainingnot DeepSource
  • Predictive analyticsnot DeepSource

DeepSource

  • Automating pull request code review for engineering teamsnot Anaconda
  • Auto-fixing detected code issues with AInot Anaconda
  • Enforcing code formatting standards automaticallynot Anaconda
  • Scanning large monorepos for quality issuesnot Anaconda
  • Running self-hosted AI review in regulated environmentsnot Anaconda

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Anaconda

  • Dependency resolution slower than pip due to SAT solver complexity
  • Not all PyPI packages available through default Anaconda repository
  • Requires paid licenses for organizations with 200+ employees
  • Larger disk footprint than minimal Python installations

DeepSource

  • Open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.
  • AI Review beyond the included credit is billed per 10K lines of code, which can add unpredictable cost.
  • Self-hosted deployment and BYOK AI are Enterprise-only features.
  • Enterprise pricing is not published and requires contacting sales.

Pricing, plan by plan

Anaconda

Free
  • FreeFree
    • 600+ pre-installed packages
    • Anaconda Navigator
    • 5GB cloud storage
  • Starter$15/month
    • 10GB cloud storage per user
    • Professional development environment
    • Team workspace controls
  • Business$50/month
    • Automated vulnerability scanning
    • Audit trails
    • Enterprise SSO

DeepSource

Free
  • Open SourceFree
    • Free for public repositories
    • 1,000 pull requests reviewed/month
    • 1,000 automated formatting runs/month
  • Team$24/month
    • Unlimited repositories and pull request reviews
    • $100 annual AI Review credit per user
    • Monorepo support
  • Enterprise$undefined/month
    • Self-hosted deployment
    • Bring-your-own-key AI Review
    • SSO

Which should you pick?

Choose Anaconda if

  • You need conda package manager.
  • You want to start without paying.
  • You work on Windows, macOS, Linux, Web/Cloud.
  • You also want environment management.
Anaconda review

Choose DeepSource if

  • You need automated pull request review.
  • You want to start without paying.
  • You work on web, api.
  • You also want ai-powered autofix.
DeepSource review

Questions people ask

Is Anaconda or DeepSource better?
Neither clearly leads. Anaconda starts at Free and DeepSource at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anaconda or DeepSource?
Anaconda starts at Free and DeepSource at Free.
Does Anaconda or DeepSource run on more platforms?
Anaconda runs on Windows, macOS, Linux, Web/Cloud. DeepSource runs on web, api.
Can I use Anaconda for free?
Both have a free tier, so you can try either at no cost before committing.
What is Anaconda best used for?
Anaconda is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what DeepSource is typically brought in for.
What can Anaconda do that DeepSource cannot?
Anaconda covers Conda package manager, Environment management, 1500+ packages, Navigator GUI. DeepSource covers Automated pull request review, AI-powered autofix, Automated code formatting, Monorepo support.

Answered from the vendors’ own pages

Anaconda: Does Anaconda have a free version?

Yes. Anaconda Distribution is free and includes 600+ pre-installed data science packages, Navigator, and 5GB of cloud storage. Organizations with 200+ employees must use paid plans unless they qualify for academic or non-profit exemptions.

Source
DeepSource: What does DeepSource cost?

The Open Source plan is free for public repos; Team is $24 per user/month billed yearly with a $100 annual AI Review credit; Enterprise is custom-priced with self-hosted options.

Source
Anaconda: What is the difference between Anaconda Distribution and Miniconda?

Anaconda Distribution includes 600+ pre-installed packages optimized for data science out of the box. Miniconda is lightweight with only conda, Python, and essential packages, requiring manual installation of additional libraries.

Source
DeepSource: Is there a free plan, and what are its limits?

Yes, the free Open Source plan covers public repositories with 1,000 pull requests reviewed per month and 1,000 automated formatting runs per month.

Source
Anaconda: Does Anaconda integrate with VS Code?

Yes. Anaconda environments can be activated in VS Code, and you can run Jupyter Notebooks directly. Both JupyterLab and conda can be managed through the VS Code Jupyter extension.

Source
DeepSource: How is AI Review usage metered?

Team plans include a $100 annual AI Review credit per user, with additional usage billed at Standard ($8/10K LOC) or Advanced ($15/10K LOC) tiers.

Source
Anaconda: What platforms does Anaconda support?

Anaconda runs on Windows, macOS, and Linux, with cloud-based deployment options. Anaconda Notebooks provides a cloud-based JupyterLab environment requiring no local installation.

Source
DeepSource: Can I change or cancel my plan?

Yes, subscriptions can be downgraded or canceled at any time.

Source
Anaconda: Do all PyPI packages work with Anaconda?

Not all PyPI packages are available through Anaconda's default conda repository. When a package is unavailable in conda, you can install it from conda-forge or pip as an alternative.

Source
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