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Groq vs Amazon Redshift ML

Groq logo

Groq

Software

Fast inference provider using proprietary LPU hardware for low-latency serving

From
On request
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Software

Create machine learning models using SQL

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Amazon Redshift ML has a free tier, so it costs nothing to try first.
  • Each has a real cost: Groq pricing is not published and is sold entirely by quote, making cost comparison difficult; 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

Where they differ

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

Attributes where Groq and Amazon Redshift ML differ
AttributeGroqAmazon Redshift ML
Starting priceOn requestFree
Pricing modelquoteusage-based
Free tierNoYes
PlatformsAPI, CloudWeb
FoundedUnknown2006

Identical on both: 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 Groq

Nothing recorded that Amazon Redshift ML does not also cover.

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.

Groq

  • Latency-sensitive applications requiring sub-second inference response timesnot Amazon Redshift ML
  • High-volume inference workloads where cost per inference matters at scalenot Amazon Redshift ML
  • Custom model deployment with performance guaranteesnot Amazon Redshift ML
  • Enterprise applications seeking inference-specific infrastructurenot Amazon Redshift ML

Amazon Redshift ML

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

Where each one falls short

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

Groq

  • Pricing is not published and is sold entirely by quote, making cost comparison difficult
  • Limited to open-weight models; no proprietary model access through the platform
  • Not widely integrated into third-party AI platforms compared to OpenAI or Anthropic

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

Groq

On request

No published plan breakdown. See the Groq 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 Groq if

  • You work on API, Cloud.
Groq 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 Groq or Amazon Redshift ML better?
Neither clearly leads. Groq starts at On request and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Groq or Amazon Redshift ML?
Amazon Redshift ML has a free tier; the other does not. Paid plans start at On request for Groq and Free for Amazon Redshift ML.
Does Groq or Amazon Redshift ML run on more platforms?
Groq runs on API, Cloud. Amazon Redshift ML runs on Web.
Can I use Amazon Redshift ML for free?
Yes. Amazon Redshift ML has a free tier, so you can try it without paying. Groq starts at On request.
What is Groq best used for?
Groq is most often used for latency-sensitive applications requiring sub-second inference response times, high-volume inference workloads where cost per inference matters at scale, custom model deployment with performance guarantees, enterprise applications seeking inference-specific infrastructure. Of those, latency-sensitive applications requiring sub-second inference response times and high-volume inference workloads where cost per inference matters at scale are not what Amazon Redshift ML is typically brought in for.
What can Groq do that Amazon Redshift ML cannot?
Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support.
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