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Machine Learning & Data Science · head to head

Dataiku vs Amazon Redshift ML

Dataiku logo

Dataiku

Machine Learning & Data Science

Everyday AI, Extraordinary People

From
Free
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; 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
  • They diverge on capability: Dataiku covers Visual data prep, Amazon Redshift ML covers SQL-based ML.

Where they differ

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

Attributes where Dataiku and Amazon Redshift ML differ
AttributeDataikuAmazon Redshift ML
Pricing modelfreemiumusage-based
PlatformsLinux, Mac, Windows, WebWeb
Founded20132006

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Dataiku

  • Visual data prep
  • MLOps
  • Collaboration
  • Governence
  • Python
  • R
  • Spark
  • Snowflake

Only in Amazon Redshift ML

  • SQL-based ML
  • SageMaker integration
  • BYOM support
  • In-database predictions
  • Amazon Redshift
  • SageMaker
  • S3
  • Glue

Both cover

  • AutoML
  • Web support

What people use each for

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

Dataiku

  • Building and deploying data science and machine learning pipelinesnot Amazon Redshift ML
  • Giving analysts and data scientists a shared visual and code environmentnot Amazon Redshift ML

Amazon Redshift ML

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

Where each one falls short

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

Dataiku

  • No pricing is published at any tier, and the plans page carries no figures at all
  • User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
  • Access begins with a demo request or a trial rather than a self serve signup

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

Dataiku

Free
  • Free EditionFree
    • Single user
    • Core features
  • EnterpriseFree
    • Full platform
    • Collaboration
    • MLOps

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 Dataiku if

  • You need visual data prep.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want mlops.
Dataiku review

Choose Amazon Redshift ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want sagemaker integration.
Amazon Redshift ML review

Questions people ask

Is Dataiku or Amazon Redshift ML better?
Neither clearly leads. Dataiku 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, Dataiku or Amazon Redshift ML?
Dataiku starts at Free and Amazon Redshift ML at Free.
Does Dataiku or Amazon Redshift ML run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Amazon Redshift ML runs on Web.
Can I use Dataiku for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dataiku best used for?
Dataiku is most often used for building and deploying data science and machine learning pipelines, giving analysts and data scientists a shared visual and code environment. Of those, building and deploying data science and machine learning pipelines and giving analysts and data scientists a shared visual and code environment are not what Amazon Redshift ML is typically brought in for.
What can Dataiku do that Amazon Redshift ML cannot?
Dataiku covers Visual data prep, MLOps, Collaboration, Governence. Amazon Redshift ML covers SQL-based ML, SageMaker integration, BYOM support, In-database predictions. Both handle AutoML, Web support.
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