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Databases · head to head

Apache Airflow vs Flowable

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Flowable logo

Flowable

Automation Integration

Apache 2.0 BPMN, CMMN and DMN engine from the team that originally built Activiti

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job; Flowable the open source engine is genuinely usable but ships without the modelling studio, work application and admin console, so an open source deployment means building your own user interfaces before anyone can use it.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Flowable covers BPMN 2.0 engine.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Airflow and Flowable actually diverge.

Attributes where Apache Airflow and Flowable differ
AttributeApache AirflowFlowable
Pricing modelOpen source, no licence fee; managed services billed separatelyquote
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, Windows, Docker, Kubernetes, Cloud
CategoryDatabasesAutomation Integration

Identical on both: starting price (Free), 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 Apache Airflow

  • Pipelines as Python
  • Web UI
  • Cloud provider packages
  • Jinja templating
  • Retries and dependencies
  • Extensible operators

Only in Flowable

  • BPMN 2.0 engine
  • CMMN case management
  • DMN decision tables
  • Spring Boot integration
  • Modelling studio
  • Task and case application
  • REST APIs
  • History and audit

What people use each for

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

Apache Airflow

  • Scheduling nightly ETL where step order and retries matternot Flowable
  • Coordinating machine learning training and evaluation runsnot Flowable
  • Orchestrating dbt runs alongside extraction and loadingnot Flowable
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Flowable

Flowable

  • An insurer automating claims handling where each case follows a different path and BPMN alone cannot express itnot Apache Airflow
  • A bank embedding process orchestration inside an existing Spring Boot estate rather than buying a separate platformnot Apache Airflow
  • A team leaving Activiti or jBPM that wants the same API family with active commercial maintenancenot Apache Airflow
  • A regulated organisation needing complete process history and decision table audit trails for supervisorsnot Apache Airflow

Where each one falls short

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

Apache Airflow

  • Self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • Built for scheduled batch work, and a poor fit for event-driven or sub-minute latency pipelines
  • Because DAGs are Python that the scheduler parses continuously, expensive top-level code in a DAG file slows the whole scheduler
  • Local development and testing of DAGs is awkward compared with newer orchestrators designed with it in mind

Flowable

  • The open source engine is genuinely usable but ships without the modelling studio, work application and admin console, so an open source deployment means building your own user interfaces before anyone can use it.
  • It expects Java engineering capacity; teams looking for a business-user low-code automation tool will find the modelling and deployment cycle far too technical.
  • Enterprise pricing is not published and is quoted per deployment, leaving buyers without a benchmark against Camunda or IBM alternatives.
  • The Activiti fork left three engines with related APIs and overlapping documentation in circulation, and search results routinely return advice for the wrong one.
  • Flowable AG is a small Swiss company relative to its competitors, so the partner network, training market and pool of engineers with production experience are all limited outside Europe.

Pricing, plan by plan

Apache Airflow

Free
  • Apache AirflowFree
    • Full scheduler and web UI
    • All provider packages
    • No task or DAG limits

Flowable

Free
  • Flowable Open SourceFree
    • Apache 2.0 licensed BPMN, CMMN and DMN engines
    • Embeddable Java library or standalone apps
    • No modelling studio or enterprise applications
  • Flowable Enterprise$undefined/year
    • Modelling studio, work application and admin console
    • Connectors, forms and advanced identity management
    • Support with SLA and version maintenance

Which should you pick?

Choose Apache Airflow if

  • You need pipelines as python.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want web ui.
Apache Airflow review

Choose Flowable if

  • You need bpmn 2.0 engine.
  • You want to start without paying.
  • You work on Linux, Windows, Docker, Kubernetes, Cloud.
  • You also want cmmn case management.
Flowable review

Questions people ask

Is Apache Airflow or Flowable better?
Neither clearly leads. Apache Airflow starts at Free and Flowable at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Flowable?
Apache Airflow starts at Free and Flowable at Free.
Does Apache Airflow or Flowable run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Flowable runs on Linux, Windows, Docker, Kubernetes, Cloud.
Can I use Apache Airflow for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Airflow best used for?
Apache Airflow is most often used for scheduling nightly etl where step order and retries matter, coordinating machine learning training and evaluation runs, orchestrating dbt runs alongside extraction and loading, replacing a sprawl of cron jobs with dependencies and visible run history. Of those, scheduling nightly etl where step order and retries matter and coordinating machine learning training and evaluation runs are not what Flowable is typically brought in for.
What can Apache Airflow do that Flowable cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Flowable covers BPMN 2.0 engine, CMMN case management, DMN decision tables, Spring Boot integration.

Answered from the vendors’ own pages

Apache Airflow: Is Apache Airflow free?

Yes. Airflow is open source under the Apache Software Foundation with no licence fee. Costs are the infrastructure to run it, or a managed service such as Google Cloud Composer or Amazon MWAA.

Flowable: Is Flowable open source?

Yes, the BPMN, CMMN and DMN engines are Apache 2.0. The modelling studio and enterprise applications are commercial.

Apache Airflow: What language are Airflow workflows written in?

Python. A workflow is a Python file, so standard language features including loops and datetime handling can generate tasks dynamically, with no XML or command-line configuration.

Flowable: How does it relate to Activiti and jBPM?

The same core developers built jBPM, then Activiti, then forked Activiti in 2016 to create Flowable.

Apache Airflow: Is Airflow suitable for real-time pipelines?

Not really. Airflow is designed for scheduled batch orchestration. Event-driven or sub-minute work is better served by a streaming platform such as Kafka or a purpose-built streaming engine.

Flowable: What does Flowable Enterprise cost?

Nothing is published. It is quoted per deployment by the vendor.

Apache Airflow: What are the main alternatives to Airflow?

Dagster and Prefect are the two most commonly weighed against it, both newer and both designed around the local development and testing experience Airflow is criticised for.

Flowable: Why choose it over Camunda?

CMMN case management is a first-class engine, which matters when work is exception-driven rather than a fixed sequence.

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