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Machine Learning · head to head

Alteryx vs JMP

Alteryx logo

Alteryx

Machine Learning

Analytics automation platform

From
$250/month
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: Alteryx starter is $250 per user per month billed annually, and the Professional and Enterprise editions are quote-only; 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: Alteryx covers Data preparation, 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 Alteryx and JMP actually diverge.

Attributes where Alteryx and JMP differ
AttributeAlteryxJMP
Starting price$250/monthFree
Free tierNoYes
PlatformsWindows, WebMac, Windows
Founded19971976

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 Alteryx

  • Data preparation
  • Data blending
  • Predictive analytics
  • Spatial analytics
  • Reporting
  • Python
  • R
  • Snowflake

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.

Alteryx

  • Data preparation and building AI-ready datasetsnot JMP
  • Predictive analytics without writing codenot JMP
  • Automating and orchestrating repeatable analytics workflowsnot JMP
  • Enterprise reporting with governed, reusable logicnot JMP
  • Connecting to Snowflake, Databricks and cloud warehouses alongside on-premises systemsnot 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 Alteryx
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Alteryx
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Alteryx
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Alteryx

Where each one falls short

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

Alteryx

  • Starter is $250 per user per month billed annually, and the Professional and Enterprise editions are quote-only
  • Automation runs are metered, with 50 included on Starter and 15,000 on Professional, and more must be bought
  • Cost depends on three separate dimensions at once: edition, user role and automation capacity
  • Advanced analytics, governance and orchestration are withheld from the entry edition

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

Alteryx

$250/month
  • Starter Edition$250/month
    • 1-10 users
    • 50 automation runs included
    • Cloud only
  • Professional Edition$null/month
    • Basic and Full users
    • 15,000 automation runs included
    • Cloud and desktop deployment
  • Enterprise Edition$null/month
    • All user types
    • 15,000 automation runs included
    • All deployment options

JMP

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

Which should you pick?

Choose Alteryx if

  • You need data preparation.
  • You work on Windows, Web.
  • You also want data blending.
Alteryx 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 Alteryx or JMP better?
Neither clearly leads. Alteryx starts at $250/month and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Alteryx or JMP?
JMP has a free tier; the other does not. Paid plans start at $250/month for Alteryx and Free for JMP.
Does Alteryx or JMP run on more platforms?
Alteryx runs on Windows, 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. Alteryx starts at $250/month.
What is Alteryx best used for?
Alteryx is most often used for data preparation and building ai-ready datasets, predictive analytics without writing code, automating and orchestrating repeatable analytics workflows, enterprise reporting with governed, reusable logic. Of those, data preparation and building ai-ready datasets and predictive analytics without writing code are not what JMP is typically brought in for.
What can Alteryx do that JMP cannot?
Alteryx covers Data preparation, Data blending, Predictive analytics, Spatial analytics. JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.

Answered from the vendors’ own pages

Alteryx: How much does Alteryx Starter cost?

Alteryx Starter Edition costs $250 USD per user per month when billed annually, for teams of 1-10 users.

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.

Alteryx: Is there a free trial for Alteryx?

Yes, Alteryx offers a 30-day free trial to evaluate the platform before committing to a paid plan.

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.

Alteryx: What differentiates Alteryx Professional from Starter?

Professional Edition supports both Basic and Full user roles, includes 15,000 automation runs, offers cloud and desktop deployment, connects to 100+ data sources, and enables advanced data preparation and macros. Professional and Enterprise editions require contacting sales for pricing.

Source
JMP: Does it run on Linux?

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

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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