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Cybersecurity · head to head

authentik vs scikit-learn

authentik logo

authentik

Cybersecurity

Open-source identity provider with flexible authentication flows

From
Free
Rated
-
Full reviewWebsite
scikit-learn logo

scikit-learn

Machine Learning

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: authentik smaller project than Keycloak, with a correspondingly smaller community and fewer integration guides; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
  • They diverge on capability: authentik covers Configurable flows, scikit-learn covers Classification algorithms.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where authentik and scikit-learn differ
Attributeauthentikscikit-learn
Pricing modelOpen-source core with a paid enterprise tierUnknown
PlatformsDocker, Kubernetes, Linux, Self-hostedPython, Linux, macOS, Windows
CategoryCybersecurityMachine Learning
FoundedUnknown2007

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 authentik

  • Configurable flows
  • Protocol support
  • Application proxy
  • Modern admin interface

Only in scikit-learn

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

What people use each for

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

authentik

  • Self-hosted SSO across internal services without commercial identity pricingnot scikit-learn
  • Putting authentication in front of applications that have none, via the proxynot scikit-learn
  • Teams who tried Keycloak and wanted something less heavynot scikit-learn

scikit-learn

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

Where each one falls short

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

authentik

  • Smaller project than Keycloak, with a correspondingly smaller community and fewer integration guides
  • The flow model is flexible but conceptually unfamiliar, and simple setups can feel over-abstracted
  • Enterprise support and some governance features sit behind the paid tier
  • Self-hosted identity is still yours to secure, patch and keep available

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

authentik

Free
  • Open sourceFree
    • Full identity provider
    • All protocols
    • Community support

scikit-learn

Free

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

Which should you pick?

Choose authentik if

  • You need configurable flows.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Linux, Self-hosted.
  • You also want protocol support.
authentik 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 authentik or scikit-learn better?
Neither clearly leads. authentik 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, authentik or scikit-learn?
authentik starts at Free and scikit-learn at Free.
Does authentik or scikit-learn run on more platforms?
authentik runs on Docker, Kubernetes, Linux, Self-hosted. scikit-learn runs on Python, Linux, macOS, Windows.
Can I use authentik for free?
Both have a free tier, so you can try either at no cost before committing.
What is authentik best used for?
authentik is most often used for self-hosted sso across internal services without commercial identity pricing, putting authentication in front of applications that have none, via the proxy, teams who tried keycloak and wanted something less heavy. Of those, self-hosted sso across internal services without commercial identity pricing and putting authentication in front of applications that have none, via the proxy are not what scikit-learn is typically brought in for.
What can authentik do that scikit-learn cannot?
authentik covers Configurable flows, Protocol support, Application proxy, Modern admin interface. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.

Answered from the vendors’ own pages

authentik: Is authentik free?

The open-source edition is free and complete for most use. An enterprise tier adds support and additional features.

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
authentik: authentik or Keycloak?

authentik is generally reported as easier to run and administer; Keycloak is more established with a larger community and Red Hat behind it.

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
authentik: Can authentik protect apps with no login of their own?

Yes. Its application proxy places authentication in front of services that have no built-in authentication.

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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