Machine Learning · head to head
JMP vs Weka
JMP
Machine Learning
Desktop statistical and design of experiments software from a SAS subsidiary
- From
- Free
- Rated
- -
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.; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- They diverge on capability: JMP covers Custom design of experiments, Weka covers Classification.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which JMP and Weka actually diverge.
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 Weka
- Classification
- Regression
- Clustering
- Association rules
- Feature selection
- Java
- R
- Python
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 Weka
- Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Weka
- Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Weka
- Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Weka
Weka
- Teaching and exploring classic machine learning algorithms through a GUInot JMP
- Running data mining experiments and preprocessing without writing codenot 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.
Weka
- The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
- Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture
Pricing, plan by plan
JMP
Free- TrialFree
- 30-day trial
- Full features
- JMP$1785/year
- Core JMP
- Standard features
Weka
Free- Open SourceFree
- All ML algorithms
- GUI and CLI
- Java API
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 Weka if
- You need classification.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want regression.
Questions people ask
- Is JMP or Weka better?
- Neither clearly leads. JMP starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, JMP or Weka?
- JMP starts at Free and Weka at Free.
- Does JMP or Weka run on more platforms?
- JMP runs on Mac, Windows. Weka runs on Linux, Mac, 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 Weka is typically brought in for.
- What can JMP do that Weka cannot?
- JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools. Weka covers Classification, Regression, Clustering, Association rules.
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.
Weka: What is the cost of Weka software?
Weka is provided at no cost as open-source software released under the GNU General Public License, making it freely available for download and use.
SourceJMP: 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.
Weka: Are there commercial licensing options available?
Yes, the project offers information about commercial licenses for organizations requiring non-GPL terms, which can be found in their commercial applications documentation.
SourceJMP: Does it run on Linux?
No. Windows and macOS only, as an installed application.
Weka: What support resources are available to users?
Multiple support avenues exist including comprehensive documentation, frequently asked questions, dedicated help resources, and access to courses for learning the platform.
SourceJMP: 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.
Weka: Is source code access provided?
Yes, developers have full access to source code through the Git repository, along with development documentation and code credits for contributors.
SourceJMP: 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.
Related pages
Other head to heads
- JMP vs DataRobot
- JMP vs AWS SageMaker
- JMP vs Google Vertex AI
- JMP vs Azure Machine Learning
- JMP vs IBM SPSS
- JMP vs Minitab
- JMP vs Stata
- JMP vs Jupyter
- JMP vs Weights & Biases
- JMP vs Orange
- JMP vs Databricks
- JMP vs Snowflake
- JMP vs PyTorch
- JMP vs scikit-learn
- JMP vs Apache Spark MLlib
- JMP vs Weaviate
- JMP vs Alteryx
- JMP vs MATLAB
- JMP vs SAS
- JMP vs ClearML
- JMP vs Mistral AI
- JMP vs Ollama
- JMP vs OpenRouter
- JMP vs BigQuery ML
- Weka vs DataRobot
- Weka vs AWS SageMaker
- Weka vs Google Vertex AI
- Weka vs Azure Machine Learning
- Weka vs IBM SPSS
- Weka vs Minitab
- Weka vs Stata
- Weka vs Jupyter
- Weka vs Weights & Biases
- Weka vs Orange
- Weka vs Databricks
- Weka vs Snowflake
- Weka vs PyTorch
- Weka vs scikit-learn
- Weka vs Apache Spark MLlib
- Weka vs Weaviate
- Weka vs Alteryx
- Weka vs MATLAB
- Weka vs SAS
- Weka vs ClearML
- Weka vs Mistral AI
- Weka vs Ollama
- Weka vs OpenRouter
- Weka vs BigQuery ML