Softwr

Machine Learning · head to head

JMP vs Lightdash

JMP logo

JMP

Machine Learning

Desktop statistical and design of experiments software from a SAS subsidiary

From
Free
Rated
-
Full reviewWebsite
Lightdash logo

Lightdash

Business Intelligence

Open-source BI for dbt users

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.; Lightdash requires existing dbt infrastructure, not suitable for teams without data models
  • They diverge on capability: JMP covers Custom design of experiments, Lightdash covers dbt Integration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which JMP and Lightdash actually diverge.

Attributes where JMP and Lightdash differ
AttributeJMPLightdash
Pricing modelsubscriptionUnknown
PlatformsMac, WindowsWeb, Cloud (managed), Self-hosted (on-premise)
CategoryMachine LearningBusiness Intelligence
Founded19762021

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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 Lightdash

  • dbt Integration
  • Metrics Layer
  • Dashboards
  • Scheduling
  • Version Control
  • dbt
  • BigQuery
  • Snowflake

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

Lightdash

  • Self-service analyticsnot JMP
  • Data explorationnot JMP
  • Ad-hoc reportingnot JMP
  • Collaborative analysisnot JMP
  • Embedded 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.

Lightdash

  • Requires existing dbt infrastructure, not suitable for teams without data models
  • Enterprise features and AI agents unavailable in open-source MIT-licensed core

Pricing, plan by plan

JMP

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

Lightdash

Free
  • Open SourceFree
    • MIT-licensed core
    • Self-hostable
    • dbt integration
  • Cloud Managed$undefined/mo
    • Managed hosting
    • Premium features
    • AI agent capabilities

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 Lightdash if

  • You need dbt integration.
  • You want to start without paying.
  • You work on Web, Cloud (managed), Self-hosted (on-premise).
  • You also want metrics layer.
Lightdash review

Questions people ask

Is JMP or Lightdash better?
Neither clearly leads. JMP starts at Free and Lightdash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or Lightdash?
JMP starts at Free and Lightdash at Free.
Does JMP or Lightdash run on more platforms?
JMP runs on Mac, Windows. Lightdash runs on Web, Cloud (managed), Self-hosted (on-premise).
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 Lightdash is typically brought in for.
What can JMP do that Lightdash cannot?
JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Lightdash covers dbt Integration, Metrics Layer, Dashboards, Scheduling.

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.

Lightdash: Is Lightdash free?

Yes. Lightdash is free and open source under the MIT license. Self-hosting is completely free. Managed cloud services and enterprise features require separate licensing.

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.

Lightdash: How does Lightdash integrate with dbt?

Lightdash reads dbt models and metric definitions directly. A team defines metrics once in dbt and reuses them across dashboards, exploration, and AI agents without redefinition.

Source
JMP: Does it run on Linux?

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

Lightdash: Does Lightdash support SQL queries?

Yes. As a modern BI platform for analysts, Lightdash supports full SQL capabilities alongside dbt model exploration and visual query builders.

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.

Lightdash: What are Lightdash AI agents?

Lightdash AI agents, available on paid plans, allow natural language queries against your data, generating SQL and visualizations automatically from questions.

Source
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.

Lightdash: Can Lightdash be self-hosted?

Yes. Lightdash's MIT-licensed core is completely self-hostable and free. Enterprise features and AI agents ship under separate licensing.

Source
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