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Machine Learning · head to head

DataRobot vs JMP

DataRobot logo

DataRobot

Machine Learning

Enterprise AI platform for automated machine learning

From
On request
Rated
-
Full reviewWebsite
JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only JMP 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; JMP it is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.
  • They diverge on capability: DataRobot covers Automated ML, JMP covers Custom design of experiments.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DataRobot and JMP actually diverge.

Attributes where DataRobot and JMP differ
AttributeDataRobotJMP
Starting priceOn requestFree
Free tierNoYes
PlatformsWebMac, Windows
Founded20121976

Identical on both: pricing model (subscription), 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 DataRobot

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

Only in JMP

  • Custom design of experiments
  • Linked interactive graphics
  • Analysis platforms
  • Quality and process tools
  • Graph Builder
  • JSL scripting
  • Scoring code export
  • Predictive modelling in JMP Pro

What people use each for

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

DataRobot

  • Machine learningnot JMP
  • Data analysisnot JMP
  • Model trainingnot JMP
  • Predictive analyticsnot JMP

JMP

  • Planning a physical experiment where each run is expensive, and the question is which twelve runs to perform rather than how to model data you already havenot DataRobot
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot DataRobot
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot DataRobot
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot 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

JMP

  • It is a desktop application holding the working table in memory, so a data set that outgrows the workstation has no in-place upgrade path, only a move to a different tool and a different skill set.
  • There is no Linux build and no server edition for running analyses, so JMP cannot sit in a scheduled pipeline the way an R or Python script can, and recurring reports depend on a named person running them on a laptop.
  • The predictive modelling capability most buyers mean when they call this machine learning software is in JMP Pro, a separate and more expensive licence, so the base product's price is not the price of the thing being evaluated.
  • JSL is proprietary to JMP, so the scripts, add-ins and automation a group accumulates over a decade do not port anywhere and become sunk cost the moment anyone questions the renewal.
  • Deployment ends at exported scoring code with no registry, monitoring or retraining, so a model that runs in production is maintained by another team in another language and steadily diverges from the version the analyst still has open.

Pricing, plan by plan

DataRobot

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

JMP

Free
  • TrialFree
    • 30-day trial
    • Full features
  • JMP$1785/year
    • Core JMP
    • Standard features

Which should you pick?

Choose DataRobot if

  • You need automated ml.
  • You also want model deployment.
DataRobot review

Choose JMP if

  • You need custom design of experiments.
  • You want to start without paying.
  • You work on Mac, Windows.
  • You also want linked interactive graphics.
JMP review

Questions people ask

Is DataRobot or JMP better?
Neither clearly leads. DataRobot starts at On request and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DataRobot or JMP?
JMP has a free tier; the other does not. Paid plans start at On request for DataRobot and Free for JMP.
Does DataRobot or JMP run on more platforms?
DataRobot runs on Web. JMP runs on Mac, Windows.
Can I use JMP for free?
Yes. JMP 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 JMP is typically brought in for.
What can DataRobot do that JMP cannot?
DataRobot covers Automated ML, Model deployment, Time series, MLOps. JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.

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
JMP: Is JMP the same thing as SAS?

No. JMP is a separate desktop product from a SAS subsidiary, with its own interface, its own scripting language and its own licence. Knowing SAS does not transfer to it beyond the statistics.

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
JMP: Do I need JMP Pro?

If you want cross validation, penalised regression, boosted trees or neural networks, yes. The base edition covers classical statistics, graphics and design of experiments well and stops short of predictive modelling.

DataRobot: Does DataRobot support generative AI?

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

Source
JMP: Does it run on Linux?

No. Windows and macOS only, as an installed application.

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
JMP: Can I put a JMP model into production?

Only by exporting the scoring formula as SQL, C, Python or similar and running it in another system. JMP itself does not serve, monitor or retrain models.

JMP: Who actually uses it?

Process and quality engineers, and scientists in R&D, particularly in semiconductor, chemicals, pharmaceutical and medical device work. It is not usually chosen by data engineering or platform teams.

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