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Machine Learning · head to head

IBM SPSS vs Seldon

IBM SPSS logo

IBM SPSS

Machine Learning

Statistical analysis software for data science

From
Free
Rated
-
Full reviewWebsite
Seldon logo

Seldon

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: IBM SPSS add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals; 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: IBM SPSS covers Statistical analysis, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which IBM SPSS and Seldon actually diverge.

Attributes where IBM SPSS and Seldon differ
AttributeIBM SPSSSeldon
Pricing modelsubscriptionfreemium
PlatformsLinux, Mac, WindowsLinux
Founded19112014

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 IBM SPSS

  • Statistical analysis
  • Predictive modeling
  • Data visualization
  • Survey analysis
  • Decision trees
  • Python
  • R
  • Excel

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.

IBM SPSS

  • Statistical testing and regression analysis for academic and market researchnot Seldon
  • Predictive modelling and forecasting without writing codenot Seldon

Seldon

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

Where each one falls short

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

IBM SPSS

  • Add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
  • Subscription cost renews at the then current price at the end of the first year, so the advertised rate applies to the first term only
  • Prices shown are described by IBM as indicative, vary by country and exclude applicable taxes and duties
  • Extended access periods of 12 months or more are handled as tailored pricing rather than a published rate
  • Advanced statistics, custom tables, decision trees and forecasting are separate add-ons rather than part of the base product

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

IBM SPSS

Free
  • TrialFree
    • 14-day trial
    • Full features
  • Base$99/month
    • Core statistics
    • Data management

Seldon

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

Which should you pick?

Choose IBM SPSS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want predictive modeling.
IBM SPSS review

Choose Seldon if

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

Questions people ask

Is IBM SPSS or Seldon better?
Neither clearly leads. IBM SPSS starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, IBM SPSS or Seldon?
IBM SPSS starts at Free and Seldon at Free.
Does IBM SPSS or Seldon run on more platforms?
IBM SPSS runs on Linux, Mac, Windows. Seldon runs on Linux.
Can I use IBM SPSS for free?
Both have a free tier, so you can try either at no cost before committing.
What is IBM SPSS best used for?
IBM SPSS is most often used for statistical testing and regression analysis for academic and market research, predictive modelling and forecasting without writing code. Of those, statistical testing and regression analysis for academic and market research and predictive modelling and forecasting without writing code are not what Seldon is typically brought in for.
What can IBM SPSS do that Seldon cannot?
IBM SPSS covers Statistical analysis, Predictive modeling, Data visualization, Survey analysis. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

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.

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.

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.

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.

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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