Softwr

Software · head to head

Dataiku vs Apache Spark MLlib

Dataiku logo

Dataiku

Software

Everyday AI, Extraordinary People

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Software

Scalable machine learning on Apache Spark

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; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Dataiku covers Visual data prep, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Dataiku and Apache Spark MLlib actually diverge.

Attributes where Dataiku and Apache Spark MLlib differ
AttributeDataikuApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsLinux, Mac, Windows, WebLinux, macOS, Windows
Founded20131999

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

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
  • AutoML
  • MLOps
  • Collaboration
  • Governence
  • Python
  • R
  • Spark

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

Both cover

  • Databricks
  • Linux support
  • Mac support
  • Windows 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 Apache Spark MLlib
  • Giving analysts and data scientists a shared visual and code environmentnot Apache Spark MLlib

Apache Spark MLlib

  • Large-scale distributed machine learning on Spark clustersnot Dataiku
  • Classification and regression with decision trees, random forests, gradient-boosted treesnot Dataiku
  • Clustering with K-means and Gaussian Mixture Modelsnot 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

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

Pricing, plan by plan

Dataiku

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

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 automl.
Dataiku review

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Dataiku or Apache Spark MLlib better?
Neither clearly leads. Dataiku starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Apache Spark MLlib?
Dataiku starts at Free and Apache Spark MLlib at Free.
Does Dataiku or Apache Spark MLlib run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can Dataiku do that Apache Spark MLlib cannot?
Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Databricks, Linux support, Mac support, Windows support.
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on Dataiku

More on Apache Spark MLlib

Keep looking

Other head to heads