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Business Intelligence · head to head

Databox vs JMP

Databox logo

Databox

Business Intelligence

KPI dashboards for business performance

From
Free
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

  • Each has a real cost: Databox data sources are the billing unit, and the $159 Pro plan still includes only 3 before charging $5.60 for each additional one; 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: Databox covers Pre-built Dashboards, 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 Databox and JMP actually diverge.

Attributes where Databox and JMP differ
AttributeDataboxJMP
PlatformsWeb, Mobile, TvMac, Windows
CategoryBusiness IntelligenceMachine Learning
Founded20111976

Identical on both: starting price (Free), pricing model (subscription), 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 Databox

  • Pre-built Dashboards
  • Goal Tracking
  • Alerts
  • Scorecards
  • Mobile App
  • HubSpot
  • Google Analytics
  • Facebook

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.

Databox

  • Building business dashboards from multiple SaaS data sourcesnot JMP
  • Tracking KPIs and metrics across marketing, sales and finance toolsnot 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 Databox
  • Process capability and control chart work in a manufacturing quality function that has to produce evidence for a customer or regulatornot Databox
  • Exploratory analysis by an engineer or scientist who will not write code but needs more than a spreadsheetnot Databox
  • Semiconductor, chemical and pharmaceutical development groups where JMP is already the shared language for reporting resultsnot Databox

Where each one falls short

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

Databox

  • Data sources are the billing unit, and the $159 Pro plan still includes only 3 before charging $5.60 for each additional one
  • The $64 Analyst plan is capped at 5 data sources and a single user
  • The free plan allows 3 data sources, 10 custom metrics and one user
  • AI credits are metered monthly, from 50 on free to 4,000 on Growth
  • Every published price assumes annual billing, with monthly costing 20% more

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

Databox

Free
  • FreeFree
    • 3 data sources
    • 1 user
    • 1 dashboard/report
  • Analyst$64/month
    • 5 data sources
    • 1 user
    • Unlimited dashboards and reports
  • Pro$159/month
    • 3 included data sources (additional at $5.60/month)
    • Unlimited users
    • Unlimited dashboards, reports, custom metrics
  • Growth$399/month
    • 3 included data sources (additional at $5.60/month)
    • Unlimited users
    • All Pro features plus full datasets and forecasting

JMP

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

Which should you pick?

Choose Databox if

  • You need pre-built dashboards.
  • You want to start without paying.
  • You work on Web, Mobile, Tv.
  • You also want goal tracking.
Databox 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 Databox or JMP better?
Neither clearly leads. Databox 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, Databox or JMP?
Databox starts at Free and JMP at Free.
Does Databox or JMP run on more platforms?
Databox runs on Web, Mobile, Tv. JMP runs on Mac, Windows.
Can I use Databox for free?
Both have a free tier, so you can try either at no cost before committing.
What is Databox best used for?
Databox is most often used for building business dashboards from multiple saas data sources, tracking kpis and metrics across marketing, sales and finance tools. Of those, building business dashboards from multiple saas data sources and tracking kpis and metrics across marketing, sales and finance tools are not what JMP is typically brought in for.
What can Databox do that JMP cannot?
Databox covers Pre-built Dashboards, Goal Tracking, Alerts, Scorecards. JMP covers Custom design of experiments, Linked interactive graphics, Analysis platforms, Quality and process tools.

Answered from the vendors’ own pages

Databox: How much does Databox cost?

Databox is free for basic use with 3 data sources and 50 AI credits. Paid plans start at $64/month for the Analyst tier, $159/month for Pro, and $399/month for Growth (most popular). Prices shown are for annual billing; monthly billing costs more. Custom enterprise pricing is available.

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.

Databox: What is the difference between Databox plans?

Free plan limits users to 1 with 3 data sources. Analyst tier allows 1 user with 5 data sources and API access. Pro tier adds unlimited users and hourly syncing. Growth tier (most popular) provides 15-minute sync, full forecasting, and a dedicated customer success manager.

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.

Databox: How many users can I add to Databox plans?

Free and Analyst tiers are limited to 1 user. Pro, Growth, and Custom tiers offer unlimited users with no per-seat fees.

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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