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Machine Learning · head to head

Amazon Redshift ML vs Stata

Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning

SQL statements in Redshift that train models on SageMaker and return them as functions

From
Free
Rated
-
Full reviewWebsite
Stata logo

Stata

Machine Learning

Data science software for research professionals

From
$48/year
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: Amazon Redshift ML training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.; Stata the entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • They diverge on capability: Amazon Redshift ML covers CREATE MODEL in SQL, Stata covers Statistical analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Amazon Redshift ML and Stata differ
AttributeAmazon Redshift MLStata
Starting priceFree$48/year
Pricing modelusage-basedsubscription
Free tierYesNo
PlatformsWebLinux, Mac, Windows
Founded20061985

Identical on both: user rating (Not yet rated), category (Machine Learning).

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

  • CREATE MODEL in SQL
  • Automatic model selection
  • Local inference
  • Bring your own model
  • Algorithm selection
  • Cost ceiling controls
  • Existing warehouse security
  • Batch and interactive scoring

Only in Stata

  • Statistical analysis
  • Data management
  • Graphics
  • Econometrics
  • Survey analysis
  • Python
  • ODBC
  • Excel

What people use each for

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

Amazon Redshift ML

  • Adding a churn or propensity score to an existing dashboard where the data is already in Redshift and nobody needs a bespoke modelnot Stata
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Stata
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Stata
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Stata

Stata

  • Statistical analysis and data analysisnot Amazon Redshift ML
  • Econometric modelingnot Amazon Redshift ML
  • Biostatistics and epidemiologynot Amazon Redshift ML
  • Academic and research data analysisnot 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

  • Training is billed by SageMaker separately from Redshift, so a feature that looks like a free SQL statement produces a second line item on a different part of the bill that the analyst who ran it usually cannot see.
  • Autopilot searches many candidate models by default and the duration and cost of CREATE MODEL scale with the data size and the MAX_CELLS setting, so an unconstrained statement against a large table is an expensive accident rather than an experiment.
  • Local inference runs on the Redshift cluster itself, so scoring millions of rows competes for the resources the warehouse exists to provide, and the remote inference alternative adds a per-batch network call plus an hourly SageMaker endpoint charge that persists whether or not anyone queries it.
  • The supported problem types are limited to what the exposed algorithms cover, so anything involving text, images, sequences, a custom loss function or a bespoke evaluation metric is out of scope and has to be built conventionally.
  • There is no retraining schedule, drift detection or model registry, so a model created by a statement stays exactly as trained until somebody remembers to recreate it, and nothing in the warehouse will report that its accuracy has decayed.

Stata

  • The entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • Raising the variable limit to 32,767 requires Stata/SE and 120,000 requires Stata/MP
  • Stata/MP is licensed by core count, so 2 core and 4 core licences are priced separately
  • Student licences require proof of enrolment at a degree granting institution
  • Stata/MP is not sold on a 6 month student term
  • Perpetual student licences cost several times the annual price, for example $298 against $94 for Stata/BE

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

Stata

$48/year
  • Stata/BE$48/year
    • Basic edition
    • Core features
  • Stata/SE$295/year
    • Standard edition
    • Larger datasets

Which should you pick?

Choose Amazon Redshift ML if

  • You need create model in sql.
  • You want to start without paying.
  • You also want automatic model selection.
Amazon Redshift ML review

Choose Stata if

  • You need statistical analysis.
  • You work on Linux, Mac, Windows.
  • You also want data management.
Stata review

Questions people ask

Is Amazon Redshift ML or Stata better?
Neither clearly leads. Amazon Redshift ML starts at Free and Stata at $48/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Redshift ML or Stata?
Amazon Redshift ML has a free tier; the other does not. Paid plans start at Free for Amazon Redshift ML and $48/year for Stata.
Does Amazon Redshift ML or Stata run on more platforms?
Amazon Redshift ML runs on Web. Stata runs on Linux, Mac, Windows.
Can I use Amazon Redshift ML for free?
Yes. Amazon Redshift ML has a free tier, so you can try it without paying. Stata starts at $48/year.
What is Amazon Redshift ML best used for?
Amazon Redshift ML is most often used for adding a churn or propensity score to an existing dashboard where the data is already in redshift and nobody needs a bespoke model, letting an analytics team test whether a predictive column has any business value before asking for data science headcount, scoring rows inside a sql pipeline where moving data out to a separate service would add fragility for little benefit, organisations committed to aws whose main constraint is a data science backlog rather than modelling sophistication. Of those, adding a churn or propensity score to an existing dashboard where the data is already in redshift and nobody needs a bespoke model and letting an analytics team test whether a predictive column has any business value before asking for data science headcount are not what Stata is typically brought in for.
What can Amazon Redshift ML do that Stata cannot?
Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model. Stata covers Statistical analysis, Data management, Graphics, Econometrics.

Answered from the vendors’ own pages

Amazon Redshift ML: Does it require SageMaker?

Yes. Redshift ML is an interface; the training happens in SageMaker and needs an IAM role and an S3 bucket for the intermediate data.

Stata: How much does Stata cost?

Stata does not publish specific pricing on its website. Customers must use the 'Order Stata' or 'Request a quote' functions to obtain pricing. StataNow is available as a subscription option, but specific monthly or annual costs are not displayed publicly.

Source
Amazon Redshift ML: Is there an extra charge?

The SQL interface is part of Redshift, but the training runs as a SageMaker job charged at SageMaker rates, and a remote inference endpoint is billed for as long as it exists.

Stata: What are the differences between Stata editions?

Stata offers multiple editions including Stata/BE and Stata/MP, with different capabilities and performance characteristics. Edition selection affects pricing, but specific comparisons and costs require requesting a quote.

Source
Amazon Redshift ML: What kinds of model can it build?

Regression, binary and multiclass classification through the automatic path, plus direct use of XGBoost, linear learner, multilayer perceptron and K-means. Anything beyond structured tabular prediction is out of scope.

Stata: Does Stata offer a subscription model?

Yes, StataNow is offered as a subscription option that delivers new features immediately upon release. However, specific pricing for StataNow subscriptions is not published on the website.

Source
Amazon Redshift ML: Can I use a model I trained myself?

Yes, through the bring-your-own-model path, either compiled into the cluster for local inference or called as a remote SageMaker endpoint.

Amazon Redshift ML: Does it retrain automatically?

No. Retraining means running CREATE MODEL again, on a schedule you build yourself, and nothing in the product monitors whether it is needed.

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