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Machine Learning & Data Science · head to head

Amazon Redshift ML vs AWS SageMaker

Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

From
Free
Rated
-
Full reviewWebsite
AWS SageMaker logo

AWS SageMaker

Machine Learning & Data Science

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite

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; AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • They diverge on capability: Amazon Redshift ML covers SQL-based ML, AWS SageMaker covers Jupyter notebooks.

Where they differ

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

Attributes where Amazon Redshift ML and AWS SageMaker differ
AttributeAmazon Redshift MLAWS SageMaker
Pricing modelusage-basedUnknown

Identical on both: starting price (Free), free tier (Yes), platforms (Web), user rating (Not yet rated), category (Machine Learning & Data Science), founded (2006).

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
  • Glue

Only in AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • Lambda
  • Step Functions
  • CloudWatch

Both cover

  • S3
  • Web support

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 AWS SageMaker

AWS SageMaker

  • 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

AWS SageMaker

  • Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
  • Does not include native job scheduling, requiring Lambda or EventBridge integration

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

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker 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.
Amazon Redshift ML review

Choose AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker review

Questions people ask

Is Amazon Redshift ML or AWS SageMaker better?
Neither clearly leads. Amazon Redshift ML starts at Free and AWS SageMaker at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Redshift ML or AWS SageMaker?
Amazon Redshift ML starts at Free and AWS SageMaker at Free.
Does Amazon Redshift ML or AWS SageMaker run on more platforms?
Both run on Web, so platform support will not decide this one for you.
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 AWS SageMaker is typically brought in for.
What can Amazon Redshift ML do that AWS SageMaker cannot?
Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support. AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Both handle S3, Web support.

Answered from the vendors’ own pages

AWS SageMaker: What is AWS SageMaker used for?

AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.

Source
AWS SageMaker: How is AWS SageMaker priced?

SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.

Source
AWS SageMaker: Does AWS SageMaker have a free tier?

Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.

Source
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