Softwr

Machine Learning · head to head

JMP vs Jupyter

JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Rated
-
Full reviewWebsite
Jupyter logo

Jupyter

Machine Learning

Interactive computing across all programming languages

From
Free
Rated
-
Full reviewWebsite

The short version

  • 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.; Jupyter notebook format makes version control and collaboration difficult with multiple contributors
  • They diverge on capability: JMP covers Custom design of experiments, Jupyter covers Interactive notebooks.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which JMP and Jupyter actually diverge.

Attributes where JMP and Jupyter differ
AttributeJMPJupyter
Pricing modelsubscriptionUnknown
PlatformsMac, WindowsWeb, Cross-platform, Linux, macOS, Windows
Founded19762014

Identical on both: starting price (Free), free tier (Yes), 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 Jupyter

  • Interactive notebooks
  • Live code execution
  • Rich visualizations
  • Markdown documentation
  • Multi-language kernels
  • Python
  • R
  • Julia

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

Jupyter

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

Jupyter

  • Notebook format makes version control and collaboration difficult with multiple contributors
  • Performance degrades with large datasets due to loading entire dataset into memory
  • Debugging capabilities limited compared to traditional IDEs
  • No paid support or commercial backing

Pricing, plan by plan

JMP

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

Jupyter

Free

No published plan breakdown. See the Jupyter review.

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.
JMP review

Choose Jupyter if

  • You need interactive notebooks.
  • You want to start without paying.
  • You work on Web, Cross-platform, Linux, macOS, Windows.
  • You also want live code execution.
Jupyter review

Questions people ask

Is JMP or Jupyter better?
Neither clearly leads. JMP starts at Free and Jupyter at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or Jupyter?
JMP starts at Free and Jupyter at Free.
Does JMP or Jupyter run on more platforms?
JMP runs on Mac, Windows. Jupyter runs on Web, Cross-platform, Linux, macOS, Windows.
Can I use JMP for free?
Both have a free tier, so you can try either at no cost before committing.
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 Jupyter is typically brought in for.
What can JMP do that Jupyter cannot?
JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Jupyter covers Interactive notebooks, Live code execution, Rich visualizations, Markdown documentation.

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.

Jupyter: Is Jupyter free to use?

Yes, Jupyter is completely free and open-source under the BSD license. There are no paid plans or commercial support requirements.

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.

Jupyter: What programming languages does Jupyter support?

Jupyter supports Python plus over 40 additional programming languages including R, Julia, Scala, and many others through different kernels.

Source
JMP: Does it run on Linux?

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

Jupyter: What is JupyterLab?

JupyterLab is the successor to classic Jupyter Notebook, adding a file browser, multiple tabs, terminal access, and an extension ecosystem for enhanced functionality.

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.

Share

Related pages

More on JMP

More on Jupyter

Keep looking

Other head to heads