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Machine Learning & Data Science · head to head

Amazon Redshift ML vs Anaconda

Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

From
Free
Rated
-
Anaconda logo

Anaconda

Machine Learning & Data Science

The world's most popular data science platform

From
Free
Rated
-

The short version

  • Each has a real cost: Amazon Redshift ML free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million; Anaconda dependency resolution slower than pip due to SAT solver complexity
  • They diverge on capability: Amazon Redshift ML covers SQL-based ML, Anaconda covers Conda package manager.

Where they differ

Only the attributes on which Amazon Redshift ML and Anaconda actually diverge.

Attributes where Amazon Redshift ML and Anaconda differ
AttributeAmazon Redshift MLAnaconda
Pricing modelusage-basedUnknown
PlatformsWebWindows, macOS, Linux, Web/Cloud
Founded20062012

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Amazon Redshift ML

  • SQL-based ML
  • AutoML
  • SageMaker integration
  • BYOM support
  • In-database predictions
  • Amazon Redshift
  • SageMaker
  • S3

Only in Anaconda

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

What people use each for

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

Amazon Redshift ML

  • Training and running machine learning models directly from SQL inside Amazon Redshiftnot Anaconda

Anaconda

  • Machine learningnot Amazon Redshift ML
  • Data analysisnot Amazon Redshift ML
  • Model trainingnot Amazon Redshift ML
  • Predictive analyticsnot Amazon Redshift ML

Where each one falls short

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

Amazon Redshift ML

  • Free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million

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

Pricing, plan by plan

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

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

Which should you pick?

Choose Amazon Redshift ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want automl.

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.

Questions people ask

Is Amazon Redshift ML or Anaconda better?
Neither clearly leads. Amazon Redshift ML starts at Free and Anaconda at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Redshift ML or Anaconda?
Amazon Redshift ML starts at Free and Anaconda at Free.
Does Amazon Redshift ML or Anaconda run on more platforms?
Amazon Redshift ML runs on Web. Anaconda runs on Windows, macOS, Linux, Web/Cloud.
Can I use Amazon Redshift ML for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Redshift ML best used for?
Amazon Redshift ML is most often used for training and running machine learning models directly from sql inside amazon redshift. Of those, training and running machine learning models directly from sql inside amazon redshift is not what Anaconda is typically brought in for.
What can Amazon Redshift ML do that Anaconda cannot?
Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support. Anaconda covers Conda package manager, Environment management, 1500+ packages, Navigator GUI.

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
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
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
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
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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