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Machine Learning · head to head

JMP vs Stata

JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Rated
-
Stata logo

Stata

Machine Learning

Data science software for research professionals

From
$48/year
Rated
-

The short version

  • Only JMP has a free tier, so it costs nothing to try first.
  • Each has a real cost: 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.; Stata the entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • They diverge on capability: JMP covers Custom design of experiments, Stata covers Statistical analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which JMP and Stata actually diverge.

Attributes where JMP and Stata differ
AttributeJMPStata
Starting priceFree$48/year
Free tierYesNo
PlatformsMac, WindowsLinux, Mac, Windows
Founded19761985

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 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

Only in Stata

  • Statistical analysis
  • Data management
  • Graphics
  • Econometrics
  • Survey analysis
  • Python
  • ODBC
  • Excel

What people use each for

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

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 Stata
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Stata
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Stata
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Stata

Stata

  • Statistical analysis and data analysisnot JMP
  • Econometric modelingnot JMP
  • Biostatistics and epidemiologynot JMP
  • Academic and research data analysisnot JMP

Where each one falls short

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

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.

Stata

  • The entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
  • Raising the variable limit to 32,767 requires Stata/SE and 120,000 requires Stata/MP
  • Stata/MP is licensed by core count, so 2 core and 4 core licences are priced separately
  • Student licences require proof of enrolment at a degree granting institution
  • Stata/MP is not sold on a 6 month student term
  • Perpetual student licences cost several times the annual price, for example $298 against $94 for Stata/BE

Pricing, plan by plan

JMP

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

Stata

$48/year
  • Stata/BE$48/year
    • Basic edition
    • Core features
  • Stata/SE$295/year
    • Standard edition
    • Larger datasets

Which should you pick?

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.

Choose Stata if

  • You need statistical analysis.
  • You work on Linux, Mac, Windows.
  • You also want data management.

Questions people ask

Is JMP or Stata better?
Neither clearly leads. JMP starts at Free and Stata at $48/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or Stata?
JMP has a free tier; the other does not. Paid plans start at Free for JMP and $48/year for Stata.
Does JMP or Stata run on more platforms?
JMP runs on Mac, Windows. Stata runs on Linux, Mac, Windows.
Can I use JMP for free?
Yes. JMP has a free tier, so you can try it without paying. Stata starts at $48/year.
What is JMP best used for?
JMP is most often used for 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 have, process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator, exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheet, semiconductor, chemical and pharmaceutical development groups where jmp is already the shared language for reporting results. Of those, 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 have and process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulator are not what Stata is typically brought in for.
What can JMP do that Stata cannot?
JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Stata covers Statistical analysis, Data management, Graphics, Econometrics.

Answered from the vendors’ own pages

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.

Stata: How much does Stata cost?

Stata does not publish specific pricing on its website. Customers must use the 'Order Stata' or 'Request a quote' functions to obtain pricing. StataNow is available as a subscription option, but specific monthly or annual costs are not displayed publicly.

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.

Stata: What are the differences between Stata editions?

Stata offers multiple editions including Stata/BE and Stata/MP, with different capabilities and performance characteristics. Edition selection affects pricing, but specific comparisons and costs require requesting a quote.

Source
JMP: Does it run on Linux?

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

Stata: Does Stata offer a subscription model?

Yes, StataNow is offered as a subscription option that delivers new features immediately upon release. However, specific pricing for StataNow subscriptions is not published on the website.

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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