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Machine Learning · head to head

Minitab vs Seldon

Minitab logo

Minitab

Machine Learning

Statistical software for quality engineering, and the tool Six Sigma training is written around

From
$2394/year
Rated
-
Seldon logo

Seldon

Machine Learning

Kubernetes model serving whose current version is licensed under the Business Source Licence

From
Free
Rated
-

The short version

  • Only Seldon has a free tier, so it costs nothing to try first.
  • Each has a real cost: Minitab licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.; Seldon seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • They diverge on capability: Minitab covers Control charts, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Minitab and Seldon actually diverge.

Attributes where Minitab and Seldon differ
AttributeMinitabSeldon
Starting price$2394/yearFree
Pricing modelsubscriptionfreemium
Free tierNoYes
PlatformsMac, Windows, WebLinux
Founded19722014

Identical on both: 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 Minitab

  • Control charts
  • Process capability analysis
  • Measurement systems analysis
  • Design of experiments
  • Classical statistics
  • Assistant
  • Predictive Analytics module
  • Desktop and browser access

Only in Seldon

  • Kubernetes custom resources
  • Inference graphs
  • Traffic strategies
  • Open Inference Protocol
  • Alibi Explain
  • Alibi Detect
  • Kafka-backed pipelines in v2
  • Commercial control plane

What people use each for

The jobs each tool is most often brought in to do.

Minitab

  • Six Sigma and process improvement projects where the training materials and internal procedures already assume Minitabnot Seldon
  • Producing capability and gage studies as evidence for a customer audit or a regulatory submissionnot Seldon
  • Design of experiments on a production process, run by an engineer who will not be writing codenot Seldon
  • Quality departments that need credible statistics without hiring a statistician or a data scientistnot Seldon

Seldon

  • Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot Minitab
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot Minitab
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot Minitab
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot Minitab

Where each one falls short

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

Minitab

  • Licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.
  • Analyses are recorded as a project file and a session log rather than as code, so reviewing what somebody did means reading output instead of reading a script, and reproducing it a year later depends on the same version still being installed.
  • The machine learning capability is a separately licensed module with a fixed set of tree-based methods, so it is neither included in the base price nor competitive with what a Python user has for nothing.
  • There is no deployment path in the statistical product, so putting a model into a running process means buying Minitab Model Ops as another product or reimplementing the model somewhere else entirely.
  • Data handling is worksheet-shaped and held in memory, so anything past a few million rows means preparing the extract in another tool first, and joins and reshaping are clumsy compared with SQL or pandas.

Seldon

  • Seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • Core v1 remains Apache 2.0 but is in maintenance, so taking the free route means running software that receives no new development while the architecture it belongs to moves on without it.
  • Version 2 is a different system rather than a newer release, with different custom resources, a scheduler component and a Kafka-based pipeline model, so migrating from v1 is a re-implementation of every deployment manifest rather than an upgrade.
  • Kafka is a dependency for v2 pipelines, so an organisation that does not already operate it takes on a distributed log with its own storage, retention, rebalancing and failure modes purely in order to serve models.
  • Everything assumes Kubernetes fluency and the failure modes are Kubernetes failure modes, custom resource version mismatches, an operator that will not reconcile, admission webhooks and resource limits terminating an inference pod mid-request, so it needs a platform engineer rather than a data scientist.

Pricing, plan by plan

Minitab

$2394/year
  • Solution Center Core$2394/year
    • Marked as Most Popular
    • Best for quality professionals
    • Minitab Dashboards
  • Solution Center Analytics$2593.5/year
    • Best for analytics professionals
    • Includes predictive analytics capabilities
    • Minitab Dashboards
  • Solution Center Copilot$2793/year
    • All-in-one platform for operational excellence
    • Includes AI-powered insights
    • Minitab Dashboards

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

Which should you pick?

Choose Minitab if

  • You need control charts.
  • You work on Mac, Windows, Web.
  • You also want process capability analysis.

Choose Seldon if

  • You need kubernetes custom resources.
  • You want to start without paying.
  • You work on Linux.
  • You also want inference graphs.

Questions people ask

Is Minitab or Seldon better?
Neither clearly leads. Minitab starts at $2394/year and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Minitab or Seldon?
Seldon has a free tier; the other does not. Paid plans start at $2394/year for Minitab and Free for Seldon.
Does Minitab or Seldon run on more platforms?
Minitab runs on Mac, Windows, Web. Seldon runs on Linux.
Can I use Seldon for free?
Yes. Seldon has a free tier, so you can try it without paying. Minitab starts at $2394/year.
What is Minitab best used for?
Minitab is most often used for six sigma and process improvement projects where the training materials and internal procedures already assume minitab, producing capability and gage studies as evidence for a customer audit or a regulatory submission, design of experiments on a production process, run by an engineer who will not be writing code, quality departments that need credible statistics without hiring a statistician or a data scientist. Of those, six sigma and process improvement projects where the training materials and internal procedures already assume minitab and producing capability and gage studies as evidence for a customer audit or a regulatory submission are not what Seldon is typically brought in for.
What can Minitab do that Seldon cannot?
Minitab covers Control charts, Process capability analysis, Measurement systems analysis, Design of experiments. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Minitab: Does Minitab run on macOS?

The installed desktop application is Windows. Mac users work through the browser version, which is included with the subscription but is not identical in every feature.

Seldon: Is Seldon open source?

Partly, and this is the thing to check before you build on it. Core v1 is Apache 2.0 but in maintenance. Core v2 was moved to the Business Source Licence in 2024, which allows evaluation but not unlicensed production use. Verify the current licence of each component you intend to run, including MLServer and the Alibi libraries.

Minitab: Is it machine learning software?

Not primarily. It is a statistics package for quality and process work. Predictive modelling exists in a separate Predictive Analytics module and is limited to tree-based methods.

Seldon: What is the difference between v1 and v2?

Architecture, not just version number. v2 introduces a scheduler, a different set of custom resources and Kafka-backed pipelines. Manifests, mental model and operations all change, so treat a move as a project.

Minitab: Can I buy a perpetual licence?

The current offer is subscription based. Older perpetual licences exist in the field but are not the way the product is sold now.

Seldon: Do I need Kubernetes?

Yes. It is a Kubernetes-native system and there is no meaningful deployment without a cluster and someone competent to run it.

Minitab: What is the difference between Minitab and Minitab Workspace or Engage?

Minitab Statistical Software does the analysis. Workspace and Engage are separate products for process mapping, project management and improvement programme governance, and are licensed separately.

Seldon: What is MLServer?

Seldon's Python inference server implementing the Open Inference Protocol, usable inside Seldon deployments or on its own. Check its current licence alongside Core's, since the company has moved projects onto the Business Source Licence.

Minitab: Can I automate it?

Only to a limited degree. There is a command language and integration options, but it is designed to be driven by a person through menus, not scheduled in a pipeline.

Seldon: Do I have to run Kafka?

For v2 pipelines, yes. If you only need single models served, that dependency is a large amount of infrastructure for the benefit, and a simpler serving layer may be the better answer.

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