Databases · head to head
Amazon Redshift vs JMP

Amazon Redshift
Databases
Fast, scalable cloud data warehouse from AWS
- From
- Free
- Rated
- -

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: Amazon Redshift on-demand pricing runs up to 75% higher than competitors like Snowflake and BigQuery; 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: Amazon Redshift covers Columnar Storage, 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 Amazon Redshift and JMP actually diverge.
| Attribute | Amazon Redshift | JMP |
|---|---|---|
| Pricing model | usage-based | subscription |
| Platforms | Web | Mac, Windows |
| Category | Databases | Machine Learning |
| Founded | 2012 | 1976 |
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 Amazon Redshift
- Columnar Storage
- Massively Parallel
- Machine Learning
- AQUA Acceleration
- Data Sharing
- Federated Query
- Concurrency Scaling
- S3
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.
Amazon Redshift
- Business intelligencenot JMP
- Data warehousingnot JMP
- Real-time analyticsnot JMP
- Reportingnot JMP
- Machine learningnot 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 Amazon Redshift
- Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Amazon Redshift
- Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Amazon Redshift
- Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Amazon Redshift
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Amazon Redshift
- On-demand pricing runs up to 75% higher than competitors like Snowflake and BigQuery
- Requires significant manual tuning including managing concurrency scaling costs and configuring Workload Management queues
- Performance degrades without proper design of distribution keys and sort keys
- Limited elastic resize options - can only halve or double current cluster size
- AWS lock-in makes it unsuitable for multi-cloud architectures
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
Amazon Redshift
Free- Free TrialFree
- 750 DC2.Large hours
- 2 months free
- Full features
- On-Demand$0.25/hour
- Pay per node hour
- All features
- Standard support
JMP
Free- TrialFree
- 30-day trial
- Full features
- JMP$1785/year
- Core JMP
- Standard features
Which should you pick?
Choose Amazon Redshift if
- You need columnar storage.
- You want to start without paying.
- You also want massively parallel.
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.
Questions people ask
- Is Amazon Redshift or JMP better?
- Neither clearly leads. Amazon Redshift starts at Free and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Amazon Redshift or JMP?
- Amazon Redshift starts at Free and JMP at Free.
- Does Amazon Redshift or JMP run on more platforms?
- Amazon Redshift runs on Web. JMP runs on Mac, Windows.
- Can I use Amazon Redshift for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Amazon Redshift best used for?
- Amazon Redshift is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what JMP is typically brought in for.
- What can Amazon Redshift do that JMP cannot?
- Amazon Redshift covers Columnar Storage, Massively Parallel, Machine Learning, AQUA Acceleration. JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.
Answered from the vendors’ own pages
Amazon Redshift: What deployment options does Amazon Redshift offer?
Redshift offers Provisioned Cluster (with RA3 or DC2 nodes) and Serverless options to match varying workloads. The new Redshift RG instance family, powered by Graviton, delivers 2.4x faster performance than RA3 at 30% lower cost per vCPU.
SourceJMP: 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.
Amazon Redshift: What does Amazon Redshift cost?
Provisioned cluster pricing: RA3 on-demand starts at $1.086/hour for ra3.xlplus. Serverless costs approximately $0.375 per RPU-hour with 4-RPU minimum (roughly $1.50/hour active workload). Managed storage costs $0.024/GB-month.
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.
Amazon Redshift: Does Redshift work with data lakes?
Yes, Redshift's integrated data lake query engine processes workloads on Apache Iceberg tables and other supported formats in Amazon S3, allowing you to run SQL analytics across your data warehouse and data lake from the same engine.
SourceJMP: Does it run on Linux?
No. Windows and macOS only, as an installed application.
Amazon Redshift: Is there a free tier for Amazon Redshift?
AWS offers a free trial with $300 USD in Serverless credits valid for 90 days, but Redshift is not part of the permanent AWS Free Tier.
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.
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.
Related pages
More on Amazon Redshift
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