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DataRobot vs Apache Spark MLlib

DataRobot logo

DataRobot

Software

Enterprise AI platform for automated machine learning

From
On request
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

  • Only Apache Spark MLlib has a free tier, so it costs nothing to try first.
  • Each has a real cost: DataRobot model transparency is limited, often resembling a black box with limited explainability; 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: DataRobot covers Automated ML, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where DataRobot and Apache Spark MLlib differ
AttributeDataRobotApache Spark MLlib
Starting priceOn requestFree
Pricing modelsubscriptionopen-source
Free tierNoYes
PlatformsWebLinux, macOS, Windows
Founded20121999

Identical on both: 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 DataRobot

  • Automated ML
  • Model deployment
  • Time series
  • MLOps
  • Model monitoring
  • Snowflake
  • AWS
  • Azure

Only in Apache Spark MLlib

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

Both cover

  • Databricks

What people use each for

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

DataRobot

  • Machine learningnot Apache Spark MLlib
  • Data analysisnot Apache Spark MLlib
  • Model trainingnot Apache Spark MLlib
  • Predictive analyticsnot Apache Spark MLlib

Apache Spark MLlib

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

Where each one falls short

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

DataRobot

  • Model transparency is limited, often resembling a black box with limited explainability
  • Requires integration with separate data manipulation tools for complex data transformation
  • Lacks native Python and R code customization for proprietary algorithms
  • Dependence on cloud connectivity means offline capabilities are not available
  • Uploading sensitive data to third-party servers raises data privacy and security concerns

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

DataRobot

On request
  • TrialFree
    • Limited access
    • Basic features
  • EnterpriseFree
    • Full platform
    • AutoML
    • MLOps

Apache Spark MLlib

Free

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

Which should you pick?

Choose DataRobot if

  • You need automated ml.
  • You also want model deployment.
DataRobot 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 DataRobot or Apache Spark MLlib better?
Neither clearly leads. DataRobot starts at On request and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DataRobot or Apache Spark MLlib?
Apache Spark MLlib has a free tier; the other does not. Paid plans start at On request for DataRobot and Free for Apache Spark MLlib.
Does DataRobot or Apache Spark MLlib run on more platforms?
DataRobot runs on Web. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Apache Spark MLlib for free?
Yes. Apache Spark MLlib has a free tier, so you can try it without paying. DataRobot starts at On request.
What is DataRobot best used for?
DataRobot is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Apache Spark MLlib is typically brought in for.
What can DataRobot do that Apache Spark MLlib cannot?
DataRobot covers Automated ML, Model deployment, Time series, MLOps. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Databricks.

Answered from the vendors’ own pages

DataRobot: Does DataRobot require data science expertise?

DataRobot automates much of the ML pipeline including data preparation, feature engineering, and model selection, making it more accessible to non-experts, though it is still an enterprise platform.

Source
DataRobot: What does DataRobot cost?

DataRobot uses custom enterprise pricing with typical starting costs around $2,500 per month for smaller organizations. For 10 users, monthly costs range from $15,000 to $20,000. Implementation and professional services are 20-40% of first-year contract value.

Source
DataRobot: Does DataRobot support generative AI?

Yes, DataRobot offers generative AI capabilities with API-first integrations for LLMs, vector databases, and embedding models.

Source
DataRobot: Can DataRobot handle unstructured data?

Yes, DataRobot supports machine learning on both structured and unstructured data, including deep learning, NLP, and image analysis.

Source
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