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Machine Learning · head to head

Orange vs Amazon Redshift ML

Orange logo

Orange

Machine Learning

Data mining and visualization toolkit

From
Free
Rated
-
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
-

The short version

  • Each has a real cost: Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL; 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: Orange covers Visual programming, 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 Orange and Amazon Redshift ML actually diverge.

Attributes where Orange and Amazon Redshift ML differ
AttributeOrangeAmazon Redshift ML
Pricing modelopen-sourceusage-based
PlatformsLinux, Mac, WindowsWeb
Founded19962006

Identical on both: starting price (Free), free tier (Yes), 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 Orange

  • Visual programming
  • Data visualization
  • Machine learning
  • Text mining
  • Bioinformatics
  • Python
  • scikit-learn
  • PyQt

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.

Orange

  • Visual programming for data mining and machine learning workflowsnot Amazon Redshift ML
  • Teaching data science without writing codenot Amazon Redshift ML
  • Exploratory data visualisation and clustering on tabular datanot 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 Orange
  • Letting an analytics team test whether a predictive column has any business value before asking for data science headcountnot Orange
  • Scoring rows inside a SQL pipeline where moving data out to a separate service would add fragility for little benefitnot Orange
  • Organisations committed to AWS whose main constraint is a data science backlog rather than modelling sophisticationnot Orange

Where each one falls short

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

Orange

  • Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
  • The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
  • Orange add-ons may carry additional licensing requirements set in their own licence files
  • Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
  • The software is distributed without any warranty of merchantability or fitness for a particular purpose

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

Orange

Free
  • Open SourceFree
    • Visual programming
    • Machine learning
    • Data visualization

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 Orange if

  • You need visual programming.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data visualization.

Choose Amazon Redshift ML if

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

Questions people ask

Is Orange or Amazon Redshift ML better?
Neither clearly leads. Orange 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, Orange or Amazon Redshift ML?
Orange starts at Free and Amazon Redshift ML at Free.
Does Orange or Amazon Redshift ML run on more platforms?
Orange runs on Linux, Mac, Windows. Amazon Redshift ML runs on Web.
Can I use Orange for free?
Both have a free tier, so you can try either at no cost before committing.
What is Orange best used for?
Orange is most often used for visual programming for data mining and machine learning workflows, teaching data science without writing code, exploratory data visualisation and clustering on tabular data. Of those, visual programming for data mining and machine learning workflows and teaching data science without writing code are not what Amazon Redshift ML is typically brought in for.
What can Orange do that Amazon Redshift ML cannot?
Orange covers Visual programming, Data visualization, Machine learning, Text mining. Amazon Redshift ML covers CREATE MODEL in SQL, Automatic model selection, Local inference, Bring your own model.

Answered from the vendors’ own pages

Orange: What is the cost of Orange Data Mining?

Orange Data Mining is free open-source software available for Windows, Mac, and other platforms. There are no subscription fees, licensing costs, or paid tiers.

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.

Orange: How is Orange Data Mining funded?

Orange Data Mining is supported through optional voluntary donations. The project encourages donations from users who value the software to support bug fixes, new features, educational content, and infrastructure maintenance.

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 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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