Softwr

Machine Learning & Data Science · head to head

PyTorch vs Amazon Redshift ML

PyTorch logo

PyTorch

Machine Learning & Data Science

Deep learning framework with dynamic computation graphs

From
Free
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: PyTorch dynamic computation graph can be less efficient for production inference than static graphs; 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
  • They diverge on capability: PyTorch covers Dynamic computation graphs, Amazon Redshift ML covers SQL-based ML.

Where they differ

Only the attributes on which PyTorch and Amazon Redshift ML actually diverge.

Attributes where PyTorch and Amazon Redshift ML differ
AttributePyTorchAmazon Redshift ML
Pricing modelUnknownusage-based
PlatformsLinux, Windows, macOSWeb
Founded20162006

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 PyTorch

  • Dynamic computation graphs
  • Automatic differentiation
  • GPU acceleration
  • Distributed training
  • TorchScript
  • TorchVision
  • TorchText
  • TorchAudio

Only in Amazon Redshift ML

  • SQL-based ML
  • AutoML
  • SageMaker integration
  • BYOM support
  • In-database predictions
  • Amazon Redshift
  • SageMaker
  • S3

What people use each for

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

PyTorch

  • Machine learningnot Amazon Redshift ML
  • Data analysisnot Amazon Redshift ML
  • Model trainingnot Amazon Redshift ML
  • Predictive analyticsnot Amazon Redshift ML

Amazon Redshift ML

  • Training and running machine learning models directly from SQL inside Amazon Redshiftnot PyTorch

Where each one falls short

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

PyTorch

  • Dynamic computation graph can be less efficient for production inference than static graphs
  • Requires more manual code for distributed training compared to some alternatives
  • Documentation focused heavily on research use cases rather than production deployment

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

Pricing, plan by plan

PyTorch

Free

No published plan breakdown. See the PyTorch review.

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

Which should you pick?

Choose PyTorch if

  • You need dynamic computation graphs.
  • You want to start without paying.
  • You work on Linux, Windows, macOS.
  • You also want automatic differentiation.
PyTorch review

Choose Amazon Redshift ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want automl.
Amazon Redshift ML review

Questions people ask

Is PyTorch or Amazon Redshift ML better?
Neither clearly leads. PyTorch starts at Free and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, PyTorch or Amazon Redshift ML?
PyTorch starts at Free and Amazon Redshift ML at Free.
Does PyTorch or Amazon Redshift ML run on more platforms?
PyTorch runs on Linux, Windows, macOS. Amazon Redshift ML runs on Web.
Can I use PyTorch for free?
Both have a free tier, so you can try either at no cost before committing.
What is PyTorch best used for?
PyTorch is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Amazon Redshift ML is typically brought in for.
What can PyTorch do that Amazon Redshift ML cannot?
PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training. Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support.

Answered from the vendors’ own pages

PyTorch: Is PyTorch free and open source?

Yes. PyTorch is an open source machine learning framework that is completely free to use. It was originally created and open-sourced by Facebook (now Meta) in 2016.

Source
PyTorch: What platforms does PyTorch support?

PyTorch supports Linux, Windows, and macOS. It provides strong GPU acceleration through CUDA and other backends for high-performance computing.

Source
PyTorch: Can I use PyTorch for production deployments?

Yes. PyTorch provides graph-based execution, distributed training, mobile deployment, and quantization features to support production deployments.

Source
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on PyTorch

More on Amazon Redshift ML

Keep looking

Other head to heads