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Business Intelligence · head to head

Amazon QuickSight vs Amazon Redshift ML

Amazon QuickSight logo

Amazon QuickSight

Business Intelligence

Scalable, serverless BI by AWS

From
$3/month
Rated
-
Full reviewWebsite
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

The short version

  • Only Amazon Redshift ML has a free tier, so it costs nothing to try first.
  • Each has a real cost: Amazon QuickSight reader and Reader Pro roles charged separately at $3 and $20/month; 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.
  • They diverge on capability: Amazon QuickSight covers SPICE In-memory Engine, Amazon Redshift ML covers CREATE MODEL in SQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Amazon QuickSight and Amazon Redshift ML differ
AttributeAmazon QuickSightAmazon Redshift ML
Starting price$3/monthFree
Pricing modelper-userusage-based
Free tierNoYes
PlatformsAWSWeb
CategoryBusiness IntelligenceMachine Learning

Identical on both: user rating (Not yet rated), 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 QuickSight

  • SPICE In-memory Engine
  • ML Insights
  • Natural Language Queries
  • Embedded Analytics
  • Pay-per-session
  • Redshift
  • S3
  • Athena

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

What people use each for

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

Amazon QuickSight

  • Business intelligencenot Amazon Redshift ML
  • Dashboard creationnot Amazon Redshift ML
  • Data visualizationnot Amazon Redshift ML

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 Amazon QuickSight
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Amazon QuickSight
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Amazon QuickSight
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Amazon QuickSight

Where each one falls short

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

Amazon QuickSight

  • Reader and Reader Pro roles charged separately at $3 and $20/month
  • Author and Author Pro roles charged at $24 and $40/month
  • $250/month infrastructure fee required if Pro users or Q&A enabled
  • SPICE storage charged at $0.38/GB monthly (10 GB included)
  • Pixel-perfect reports start at $500/month for 500 monthly units
  • Alerts charged at $0.05-$0.50 per 1,000 metrics evaluated

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.

Pricing, plan by plan

Amazon QuickSight

$3/month
  • Reader$3/month
    • Dashboard viewing only
  • Reader Pro$20/month
    • Enhanced reader capabilities
  • Author$24/month
    • Dashboard creation and editing
  • Author Pro$40/month
    • Advanced authoring features

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 Amazon QuickSight if

  • You need spice in-memory engine.
  • You work on AWS.
  • You also want ml insights.
Amazon QuickSight review

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

Questions people ask

Is Amazon QuickSight or Amazon Redshift ML better?
Neither clearly leads. Amazon QuickSight starts at $3/month and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon QuickSight or Amazon Redshift ML?
Amazon Redshift ML has a free tier; the other does not. Paid plans start at $3/month for Amazon QuickSight and Free for Amazon Redshift ML.
Does Amazon QuickSight or Amazon Redshift ML run on more platforms?
Amazon QuickSight runs on AWS. 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. Amazon QuickSight starts at $3/month.
What is Amazon QuickSight best used for?
Amazon QuickSight is most often used for business intelligence, dashboard creation, data visualization. Of those, business intelligence and dashboard creation are not what Amazon Redshift ML is typically brought in for.
What can Amazon QuickSight do that Amazon Redshift ML cannot?
Amazon QuickSight covers SPICE In-memory Engine, ML Insights, Natural Language Queries, Embedded Analytics. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Amazon QuickSight: What does Amazon QuickSight cost per user?

QuickSight pricing varies by user role. Readers start at $3/month, Reader Pro at $20/month, Authors at $24/month, and Author Pro at $40/month. All prices are per user per month.

Source
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.

Amazon QuickSight: Does QuickSight charge an infrastructure fee?

Yes, QuickSight charges an infrastructure fee of $250/month per account if the account has at least one Pro user, has Q&A enabled via topics, or has dashboard Q&A enabled.

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.

Amazon QuickSight: What are QuickSight's session capacity pricing options?

Session capacity pricing starts at $250/month for 500 sessions. Annual plans range from $20,000/year for 50,000 sessions to $258,000/year for 1,600,000 sessions, with volume discounts reducing unit costs from $0.50 to $0.16 per additional session.

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.

Amazon QuickSight: How much does additional SPICE storage cost?

Additional SPICE storage beyond the included 10 GB costs $0.38 per GB per month. Authors receive 10 GB included, but Readers do not.

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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