Machine Learning & Data Science · head to head
Amazon Redshift ML vs scikit-learn
Amazon Redshift ML
Machine Learning & Data Science
Create machine learning models using SQL
- From
- Free
- Rated
- -
scikit-learn
Machine Learning & Data Science
Machine learning in Python
- 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; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
- They diverge on capability: Amazon Redshift ML covers SQL-based ML, scikit-learn covers Classification algorithms.
Where they differ
Only the attributes on which Amazon Redshift ML and scikit-learn actually diverge.
| Attribute | Amazon Redshift ML | scikit-learn |
|---|---|---|
| Pricing model | usage-based | Unknown |
| Platforms | Web | Python, Linux, macOS, Windows |
| Founded | 2006 | 2007 |
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 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.
Amazon Redshift ML
- Training and running machine learning models directly from SQL inside Amazon Redshiftnot scikit-learn
scikit-learn
- 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
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
Amazon Redshift ML
Free- Free TrialFree
- 2-month trial
- 750 DC2.Large hours
- On-Demand$0.25/hour
- Per-node pricing
- SageMaker training
scikit-learn
FreeNo published plan breakdown. See the scikit-learn review.
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 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.
Questions people ask
- Is Amazon Redshift ML or scikit-learn better?
- Neither clearly leads. Amazon Redshift ML 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, Amazon Redshift ML or scikit-learn?
- Amazon Redshift ML starts at Free and scikit-learn at Free.
- Does Amazon Redshift ML or scikit-learn run on more platforms?
- Amazon Redshift ML runs on Web. scikit-learn runs on Python, Linux, macOS, Windows.
- 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 scikit-learn is typically brought in for.
- What can Amazon Redshift ML do that scikit-learn cannot?
- Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.
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.
Sourcescikit-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.
Sourcescikit-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.
Sourcescikit-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.
Sourcescikit-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.
Sourcescikit-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.
SourceRelated pages
More on Amazon Redshift ML
More on scikit-learn
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