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Amplitude vs scikit-learn

Amplitude logo

Amplitude

Software

The digital analytics platform to understand your users

From
Free
Rated
-
Full reviewWebsite
S

scikit-learn

Software

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Amplitude metered on event volume, so instrumenting more of a product raises the bill even if the audience does not grow; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
  • They diverge on capability: Amplitude covers Event tracking, scikit-learn covers Classification algorithms.

Where they differ

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

Attributes where Amplitude and scikit-learn differ
AttributeAmplitudescikit-learn
PlatformsWeb, Ios, Android, ApiPython, Linux, macOS, Windows
Founded20122007

Identical on both: starting price (Free), pricing model (Unknown), free tier (Yes), 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 Amplitude

  • Event tracking
  • User segmentation
  • Funnel analysis
  • Retention analysis
  • Cohort analysis
  • A/B testing
  • Revenue analytics
  • Predictive analytics

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.

Amplitude

  • User behavior analysisnot scikit-learn
  • Feature adoption trackingnot scikit-learn
  • Conversion rate optimizationnot scikit-learn
  • Customer journey mappingnot scikit-learn
  • Retention improvementnot scikit-learn

scikit-learn

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

Where each one falls short

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

Amplitude

  • Metered on event volume, so instrumenting more of a product raises the bill even if the audience does not grow
  • The free plan covers 2M events a month
  • The Plus plan scales to 70M events, above which pricing is custom
  • Growth and Enterprise pricing is not published

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

Amplitude

Free
  • StarterFree
    • 2 million events per month
  • Plus$49/month
    • $0.049 per MTU
    • Up to 300k MTUs
    • Advanced analytics
  • GrowthFree
    • Causal insights
    • Feature experimentation
    • Real-time streaming
  • EnterpriseFree
    • Cross-product analysis
    • Advanced permissions
    • Dedicated account manager

scikit-learn

Free

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

Which should you pick?

Choose Amplitude if

  • You need event tracking.
  • You want to start without paying.
  • You work on Web, Ios, Android, Api.
  • You also want user segmentation.
Amplitude 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 Amplitude or scikit-learn better?
Neither clearly leads. Amplitude 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, Amplitude or scikit-learn?
Amplitude starts at Free and scikit-learn at Free.
Does Amplitude or scikit-learn run on more platforms?
Amplitude runs on Web, Ios, Android, Api. scikit-learn runs on Python, Linux, macOS, Windows.
Can I use Amplitude for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amplitude best used for?
Amplitude is most often used for user behavior analysis, feature adoption tracking, conversion rate optimization, customer journey mapping. Of those, user behavior analysis and feature adoption tracking are not what scikit-learn is typically brought in for.
What can Amplitude do that scikit-learn cannot?
Amplitude covers Event tracking, User segmentation, Funnel analysis, Retention analysis. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.

Answered from the vendors’ own pages

Amplitude: Does Amplitude have a free plan?

Yes, Amplitude offers a free Starter plan with 2 million events per month and access to the entire platform including analytics, session replay, and experimentation features.

Source
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
Amplitude: What is Amplitude's pricing based on?

Amplitude's pricing is based on the number of monthly tracked users (MTUs), data volume, and advanced features selected. The Plus plan starts at $49 per month with a rate of $0.049 per MTU.

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
Amplitude: What analytics features does every Amplitude plan include?

Every plan includes access to the full platform: analytics, session replay, feature experimentation, web experimentation, guides and surveys, activation, and AI tools like AI Feedback and AI Assistant.

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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