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Machine Learning & Data Science · head to head

SAS vs scikit-learn

SAS logo

SAS

Machine Learning & Data Science

Analytics, AI and data management software

From
Free
Rated
-
Full reviewWebsite
S

scikit-learn

Machine Learning & Data Science

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: SAS sAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
  • They diverge on capability: SAS covers Statistical analysis, scikit-learn covers Classification algorithms.

Where they differ

Only the attributes on which SAS and scikit-learn actually diverge.

Attributes where SAS and scikit-learn differ
AttributeSASscikit-learn
Pricing modelsubscriptionUnknown
PlatformsLinux, Windows, WebPython, Linux, macOS, Windows
Founded19762007

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 SAS

  • Statistical analysis
  • Machine learning
  • Forecasting
  • Text analytics
  • Optimization
  • Python
  • R
  • Hadoop

Only in scikit-learn

  • Classification algorithms
  • Regression models
  • Clustering methods
  • Dimensionality reduction
  • Model selection
  • NumPy
  • SciPy
  • Pandas

Both cover

  • Linux support
  • Windows support

What people use each for

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

SAS

  • Regulated statistical analysis and clinical reportingnot scikit-learn
  • Enterprise data management, visualization and decisioning on one licensed platformnot scikit-learn

scikit-learn

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

Where each one falls short

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

SAS

  • SAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
  • Most new and existing customers are routed through authorized resellers rather than buying direct
  • Cloud marketplace purchases require choosing between pay as you go and bring your own licence, each with different licensing terms

scikit-learn

  • No GPU acceleration by default; limited optional GPU support requires external arrays
  • Single-machine only; no built-in distributed computing across clusters
  • All datasets must fit entirely in RAM; no out-of-core learning
  • No production-grade deep learning; neural network support limited to basic multilayer perceptron
  • No reinforcement learning algorithms

Pricing, plan by plan

SAS

Free
  • SAS OnDemand for AcademicsFree
    • Academic use
    • Core SAS
  • SAS ViyaFree
    • Full platform
    • Cloud-native
    • AI/ML

scikit-learn

Free

No published plan breakdown. See the scikit-learn review.

Which should you pick?

Choose SAS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Windows, Web.
  • You also want machine learning.
SAS review

Choose scikit-learn if

  • You need classification algorithms.
  • You want to start without paying.
  • You work on Python, Linux, macOS, Windows.
  • You also want regression models.
scikit-learn review

Questions people ask

Is SAS or scikit-learn better?
Neither clearly leads. SAS starts at Free and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, SAS or scikit-learn?
SAS starts at Free and scikit-learn at Free.
Does SAS or scikit-learn run on more platforms?
SAS runs on Linux, Windows, Web. scikit-learn runs on Python, Linux, macOS, Windows.
Can I use SAS for free?
Both have a free tier, so you can try either at no cost before committing.
What is SAS best used for?
SAS is most often used for regulated statistical analysis and clinical reporting, enterprise data management, visualization and decisioning on one licensed platform. Of those, regulated statistical analysis and clinical reporting and enterprise data management, visualization and decisioning on one licensed platform are not what scikit-learn is typically brought in for.
What can SAS do that scikit-learn cannot?
SAS covers Statistical analysis, Machine learning, Forecasting, Text analytics. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction. Both handle Linux support, Windows support.

Answered from the vendors’ own pages

scikit-learn: Does scikit-learn support GPU acceleration?

Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.

Source
scikit-learn: Can scikit-learn handle datasets larger than RAM?

No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.

Source
scikit-learn: Is scikit-learn free to use commercially?

Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.

Source
scikit-learn: What neural network capabilities does scikit-learn have?

Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.

Source
scikit-learn: Does scikit-learn include natural language processing?

Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.

Source
scikit-learn: When was scikit-learn first released?

Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.

Source
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