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Software · head to head

scikit-learn vs Stata

S

scikit-learn

Software

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite
Stata logo

Stata

Software

Data science software for research professionals

From
$48/year
Rated
-
Full reviewWebsite

The short version

  • Only scikit-learn has a free tier, so it costs nothing to try first.
  • Each has a real cost: scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays; Stata the entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • They diverge on capability: scikit-learn covers Classification algorithms, Stata covers Statistical analysis.

Where they differ

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

Attributes where scikit-learn and Stata differ
Attributescikit-learnStata
Starting priceFree$48/year
Pricing modelUnknownsubscription
Free tierYesNo
PlatformsPython, Linux, macOS, WindowsLinux, Mac, Windows
Founded20071985

Identical on both: user rating (Not yet rated), category (Unknown).

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 scikit-learn

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

Only in Stata

  • Statistical analysis
  • Data management
  • Graphics
  • Econometrics
  • Survey analysis
  • Python
  • ODBC
  • Excel

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

scikit-learn

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

Stata

  • Statistical analysis and econometrics on panel and survey datanot scikit-learn
  • Reproducible research with do files and logsnot scikit-learn
  • Teaching quantitative methods to studentsnot scikit-learn

Where each one falls short

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

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

Stata

  • The entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • Raising the variable limit to 32,767 requires Stata/SE and 120,000 requires Stata/MP
  • Stata/MP is licensed by core count, so 2 core and 4 core licences are priced separately
  • Student licences require proof of enrolment at a degree granting institution
  • Stata/MP is not sold on a 6 month student term
  • Perpetual student licences cost several times the annual price, for example $298 against $94 for Stata/BE

Pricing, plan by plan

scikit-learn

Free

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

Stata

$48/year
  • Stata/BE$48/year
    • Basic edition
    • Core features
  • Stata/SE$295/year
    • Standard edition
    • Larger datasets

Which should you pick?

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

Choose Stata if

  • You need statistical analysis.
  • You work on Linux, Mac, Windows.
  • You also want data management.
Stata review

Questions people ask

Is scikit-learn or Stata better?
Neither clearly leads. scikit-learn starts at Free and Stata at $48/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, scikit-learn or Stata?
scikit-learn has a free tier; the other does not. Paid plans start at Free for scikit-learn and $48/year for Stata.
Does scikit-learn or Stata run on more platforms?
scikit-learn runs on Python, Linux, macOS, Windows. Stata runs on Linux, Mac, Windows.
Can I use scikit-learn for free?
Yes. scikit-learn has a free tier, so you can try it without paying. Stata starts at $48/year.
What is scikit-learn best used for?
scikit-learn is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Stata is typically brought in for.
What can scikit-learn do that Stata cannot?
scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction. Stata covers Statistical analysis, Data management, Graphics, Econometrics. Both handle Linux support, Mac 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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