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Spreadsheets · head to head

Redash vs Amazon Redshift ML

Redash logo

Redash

Spreadsheets

Connect and visualize your data

From
Free
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

  • Each has a real cost: Redash pricing model not disclosed on dedicated pricing page; 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: Redash covers SQL Query Editor, 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 Redash and Amazon Redshift ML actually diverge.

Attributes where Redash and Amazon Redshift ML differ
AttributeRedashAmazon Redshift ML
Pricing modelfreemiumusage-based
PlatformsWeb, Self-hosted, CloudWeb
CategorySpreadsheetsMachine Learning
Founded20132006

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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 Redash

  • SQL Query Editor
  • Multiple Data Sources
  • Visualizations
  • Dashboards
  • Alerts
  • PostgreSQL
  • MySQL
  • BigQuery

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.

Redash

  • Data visualization and business intelligence for analyticsnot Amazon Redshift ML
  • Query result sharing and collaborative dashboard creationnot 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 Redash
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Redash
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Redash
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Redash

Where each one falls short

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

Redash

  • Pricing model not disclosed on dedicated pricing page
  • Open-source offering may require self-hosting technical expertise
  • Managed hosting or commercial support pricing not published

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

Redash

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support
  • Cloud$49/month
    • Managed Hosting
    • Automatic Updates
    • Support

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 Redash if

  • You need sql query editor.
  • You want to start without paying.
  • You work on Web, Self-hosted, Cloud.
  • You also want multiple data sources.
Redash 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 Redash or Amazon Redshift ML better?
Neither clearly leads. Redash 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, Redash or Amazon Redshift ML?
Redash starts at Free and Amazon Redshift ML at Free.
Does Redash or Amazon Redshift ML run on more platforms?
Redash runs on Web, Self-hosted, Cloud. Amazon Redshift ML runs on Web.
Can I use Redash for free?
Both have a free tier, so you can try either at no cost before committing.
What is Redash best used for?
Redash is most often used for data visualization and business intelligence for analytics, query result sharing and collaborative dashboard creation. Of those, data visualization and business intelligence for analytics and query result sharing and collaborative dashboard creation are not what Amazon Redshift ML is typically brought in for.
What can Redash do that Amazon Redshift ML cannot?
Redash covers SQL Query Editor, Multiple Data Sources, Visualizations, Dashboards. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Redash: What is Redash's pricing?

Redash is a popular open-source project with no pricing tiers listed on the pricing page. The project emphasizes no vendor lock-in and community contribution. Paid managed hosting or commercial support options may be available but are not published on this page.

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 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 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 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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