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Automation Integration · head to head

Kogito vs Mage AI

Kogito logo

Kogito

Automation Integration

Cloud-native business automation for Quarkus, now an Apache KIE component

From
Free
Rated
-
Full reviewWebsite
Mage AI logo

Mage AI

Automation Integration

Data pipeline platform with AI-generated workflows and governance

From
$100/month
Rated
-
Full reviewWebsite

The short version

  • Only Kogito has a free tier, so it costs nothing to try first.
  • Each has a real cost: Kogito kogito is a developer framework, not a product, so there is no equivalent of Camunda Operate for business users and any process monitoring interface has to be built or bought separately.; Mage AI usage-based pricing lacks transparency for cost forecasting
  • They diverge on capability: Kogito covers Build-time code generation, Mage AI covers AI-generated workflows.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Kogito and Mage AI actually diverge.

Attributes where Kogito and Mage AI differ
AttributeKogitoMage AI
Starting priceFree$100/month
Pricing modelOpen source, no licence feeUsage-based cloud platform
Free tierYesNo
PlatformsLinux, Docker, KubernetesCloud, Hybrid, Private Cloud, On-Premises

Identical on both: user rating (Not yet rated), category (Automation Integration).

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 Kogito

  • Build-time code generation
  • Quarkus and Spring Boot support
  • DMN decision services
  • Drools rules engine
  • Serverless workflow
  • Kubernetes operator

Only in Mage AI

  • AI-generated workflows
  • Pipeline building
  • Data validation
  • Workflow orchestration
  • Automatic recovery
  • Reusable components
  • Governance controls

What people use each for

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

Kogito

  • A Quarkus microservice that must expose a DMN decision model as a REST endpoint with millisecond start-upnot Mage AI
  • Serverless deployment of business rules where a traditional BPM server would be far too heavynot Mage AI
  • A Red Hat shop that wants the upstream of Red Hat process automation with the option of a supported build laternot Mage AI
  • Replacing hand-coded conditional logic with DMN tables that business analysts can review and amendnot Mage AI

Mage AI

  • Building and orchestrating data pipelines with visual interfacenot Kogito
  • Automating ETL workflows with AI assistancenot Kogito
  • Validating data quality across transformationsnot Kogito
  • Distributing transformed data to multiple destinationsnot Kogito

Where each one falls short

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

Kogito

  • Kogito is a developer framework, not a product, so there is no equivalent of Camunda Operate for business users and any process monitoring interface has to be built or bought separately.
  • Long-running stateful processes need external persistence and messaging that you configure and operate yourself, which removes much of the convenience a BPM server normally provides.
  • It sits inside the Apache KIE incubator, and incubating status means graduation is not guaranteed and the project name and artefact coordinates have already changed once.
  • Red Hat is by far the dominant contributor despite ASF stewardship, so the roadmap follows Red Hat product priorities rather than community demand.
  • Documentation is spread across legacy JBoss sites, the old Kogito site and the new Apache KIE site, and search results routinely land on outdated versions, which costs real time during adoption.

Mage AI

  • Usage-based pricing lacks transparency for cost forecasting
  • Limited standalone pricing details on website
  • Requires contact for enterprise deployment options
  • Smaller ecosystem compared to established competitors
  • May require significant customization for complex data models

Pricing, plan by plan

Kogito

Free
  • KogitoFree
    • Apache 2.0 licence
    • Apache KIE incubating project
    • No usage limits

Mage AI

$100/month
  • Cloud$100/month
    • 1 development environment
    • Unlimited users
    • Usage-based infrastructure pricing
  • Hybrid Cloud$null/custom
    • Private data processing
    • Custom infrastructure
    • Contact sales
  • Private Cloud$null/custom
    • Complete isolation
    • Full infrastructure control
    • Contact sales
  • On-Premises$null/custom
    • Full local control
    • Enterprise deployment
    • Contact sales

Which should you pick?

Choose Kogito if

  • You need build-time code generation.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want quarkus and spring boot support.
Kogito review

Choose Mage AI if

  • You need ai-generated workflows.
  • You work on Cloud, Hybrid, Private Cloud, On-Premises.
  • You also want pipeline building.
Mage AI review

Questions people ask

Is Kogito or Mage AI better?
Neither clearly leads. Kogito starts at Free and Mage AI at $100/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Kogito or Mage AI?
Kogito has a free tier; the other does not. Paid plans start at Free for Kogito and $100/month for Mage AI.
Does Kogito or Mage AI run on more platforms?
Kogito runs on Linux, Docker, Kubernetes. Mage AI runs on Cloud, Hybrid, Private Cloud, On-Premises.
Can I use Kogito for free?
Yes. Kogito has a free tier, so you can try it without paying. Mage AI starts at $100/month.
What is Kogito best used for?
Kogito is most often used for a quarkus microservice that must expose a dmn decision model as a rest endpoint with millisecond start-up, serverless deployment of business rules where a traditional bpm server would be far too heavy, a red hat shop that wants the upstream of red hat process automation with the option of a supported build later, replacing hand-coded conditional logic with dmn tables that business analysts can review and amend. Of those, a quarkus microservice that must expose a dmn decision model as a rest endpoint with millisecond start-up and serverless deployment of business rules where a traditional bpm server would be far too heavy are not what Mage AI is typically brought in for.
What can Kogito do that Mage AI cannot?
Kogito covers Build-time code generation, Quarkus and Spring Boot support, DMN decision services, Drools rules engine. Mage AI covers AI-generated workflows, Pipeline building, Data validation, Workflow orchestration.

Answered from the vendors’ own pages

Kogito: Is Kogito still maintained?

Yes. It is an Apache KIE incubating project with active commits, with Red Hat as the dominant contributor.

Mage AI: What is the starting price for Mage Cloud?

Cloud plan starts at $100/month for one development environment with unlimited users, plus usage-based compute charges.

Source
Kogito: How does it differ from jBPM?

Kogito compiles process and rule definitions into application code at build time; jBPM was a runtime engine that loads definitions.

Mage AI: How is compute usage billed on Mage?

CPU is charged at $0.50 per hour and RAM at $0.50 per 4GB per hour of utilization.

Source
Kogito: Does it need Quarkus?

It is designed for Quarkus and supports Spring Boot; both are Java frameworks rather than a standalone server.

Kogito: Is there commercial support?

Not from Apache. Red Hat sells supported builds of this lineage as part of its subscriptions.

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