Apache Airflow vs jBPM

Apache Airflow9.2Visit jBPM9.0Visit

Higher score Apache Airflow #2 in Workflow Orchestration Software 9.2/10 Free plan Free plan✓ 4 of 5 features Visit Apache Airflow

vs

jBPM #4 in Workflow Orchestration Software 9.0/10 Open source ✓ 4 of 5 features Visit jBPM

• Apache Airflow fits best

  Mature open-source data workflows

• jBPM fits best

  Java BPMN and rules-based processes

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Side by side

Feature	Apache Airflow 9.2/10 Visit ↗	jBPM 9.0/10 Visit ↗
At a glance
Editor score	9.2	9.0
Ranking	#2 in Workflow Orchestration Software	#4 in Workflow Orchestration Software
Best for	Mature open-source data workflows	Java BPMN and rules-based processes
Pricing model	Free	Free
Starting price	Free plan	Open source
Free plan	✓ (best)	Not checked yet
Free trial	—	—
Deployment	Self-hosted	Self-hosted, Browser extension
Platforms	Web	Web
Support	Community, Docs	Community, Docs
Built for	Small business, Mid-market, Enterprise	Mid-market, Enterprise
Features Apache Airflow 4/5 · jBPM 4/5
Visual workflow builder	—	✓ (best)
Event triggers	✓	✓
Automatic retries	✓	✓
Execution observability	✓	✓
Human approvals	✓ (best)	Not checked yet
Specs
Deployment model	Self-hosted	Self-hosted
Our review
Pros	Python-based DAG authoring with dependencies and scheduling Event-driven execution, retries, monitoring, and execution logs Human approvals, provider packages, and REST API access	BPMN 2.0 modeling with web and IDE-based graphical modelers Persistent long-running processes with migration and monitoring Rules, retries, events, and OpenTelemetry tracing in one engine
Cons	Self-hosted deployment requires teams to manage the environment No visual workflow builder for drag-and-drop authoring Python-based authoring may not suit teams avoiding code-defined workflows	Self-hosted deployment requires teams to operate the platform Designed for Java applications rather than standalone hosted SaaS Current Apache KIE delivery places jBPM inside Kogito
Our verdict	Apache Airflow is an open-source workflow orchestration platform for teams that define and operate data pipelines, machine-learning workflows, infrastructure automation, and other batch-oriented processes. Workflows are authored in Python… Read the review →	jBPM is an open-source workflow engine for developers building domain-specific business applications and process services in Java. It models and executes BPMN 2.0 processes, with graphical modelers available through web and IDE-based… Read the review →

Strengths and trade-offs

• Apache Airflow — where it wins

  • Python-based DAG authoring with dependencies and scheduling
  • Event-driven execution, retries, monitoring, and execution logs
  • Human approvals, provider packages, and REST API access

  Where it doesn't

  • Self-hosted deployment requires teams to manage the environment
  • No visual workflow builder for drag-and-drop authoring
  • Python-based authoring may not suit teams avoiding code-defined workflows

• jBPM — where it wins

  • BPMN 2.0 modeling with web and IDE-based graphical modelers
  • Persistent long-running processes with migration and monitoring
  • Rules, retries, events, and OpenTelemetry tracing in one engine

  Where it doesn't

  • Self-hosted deployment requires teams to operate the platform
  • Designed for Java applications rather than standalone hosted SaaS
  • Current Apache KIE delivery places jBPM inside Kogito

• Apache Airflow9.2/10 · Free plan

  A mature self-hosted choice for teams building Python-based data workflows.

  Visit Apache AirflowFull verdict →
• jBPM9.0/10 · Open source

  A developer-focused engine for durable BPMN, rules, events, and human-task workflows.

  Visit jBPMFull verdict →