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Databases · head to head

Apache Airflow vs Eclipse Mosquitto

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Eclipse Mosquitto logo

Eclipse Mosquitto

Networking

Small, EPL-licensed MQTT broker that runs on hardware other brokers cannot

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; Eclipse Mosquitto there is no clustering: Mosquitto is a single process, so high availability means building your own failover and accepting session loss on switchover.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Eclipse Mosquitto covers MQTT 5.0 support.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Airflow and Eclipse Mosquitto actually diverge.

Attributes where Apache Airflow and Eclipse Mosquitto differ
AttributeApache AirflowEclipse Mosquitto
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, no licence fee
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, Windows, macOS, Docker
CategoryDatabasesNetworking

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 Eclipse Mosquitto

  • MQTT 5.0 support
  • Very small footprint
  • Bridging
  • WebSockets listener
  • Command line clients
  • Dynamic security plugin

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 Eclipse Mosquitto
  • Coordinating machine learning training and evaluation runsnot Eclipse Mosquitto
  • Orchestrating dbt runs alongside extraction and loadingnot Eclipse Mosquitto
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Eclipse Mosquitto

Eclipse Mosquitto

  • A home or building automation stack where the broker must run on the same small computer as everything elsenot Apache Airflow
  • An industrial gateway that buffers local telemetry and bridges selected topics to a cloud brokernot Apache Airflow
  • Local development and testing of MQTT clients without provisioning a cloud IoT servicenot Apache Airflow
  • An air-gapped deployment where a broker with no licence server and no phone-home behaviour is a requirementnot 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

Eclipse Mosquitto

  • There is no clustering: Mosquitto is a single process, so high availability means building your own failover and accepting session loss on switchover.
  • Persistence is a local file rather than a replicated store, so a disk failure or an unclean shutdown can lose retained messages and queued QoS traffic.
  • Practical capacity is a few thousand concurrent clients on typical hardware, so a growing device fleet eventually forces a migration to a clustered broker.
  • The Eclipse Public Licence is weak copyleft rather than permissive, which some legal teams treat as a blocker when embedding the broker in a shipped commercial product.
  • There is no commercial support to buy from the project, so production incidents rely on community mailing lists or on paying a third party who happens to know the codebase.

Pricing, plan by plan

Apache Airflow

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

Eclipse Mosquitto

Free
  • Eclipse MosquittoFree
    • Eclipse Public License 2.0 with Eclipse Distribution Licence
    • MQTT 5.0, 3.1.1 and 3.1
    • No client or message limits beyond your hardware

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 Eclipse Mosquitto if

  • You need mqtt 5.0 support.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, Docker.
  • You also want very small footprint.
Eclipse Mosquitto review

Questions people ask

Is Apache Airflow or Eclipse Mosquitto better?
Neither clearly leads. Apache Airflow starts at Free and Eclipse Mosquitto at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Eclipse Mosquitto?
Apache Airflow starts at Free and Eclipse Mosquitto at Free.
Does Apache Airflow or Eclipse Mosquitto run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Eclipse Mosquitto runs on Linux, Windows, macOS, Docker.
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 Eclipse Mosquitto is typically brought in for.
What can Apache Airflow do that Eclipse Mosquitto cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Eclipse Mosquitto covers MQTT 5.0 support, Very small footprint, Bridging, WebSockets listener.

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.

Eclipse Mosquitto: Can Mosquitto be clustered?

No. It is a single process. High availability requires an external failover arrangement you build yourself.

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.

Eclipse Mosquitto: What licence is it?

Eclipse Public License 2.0 alongside the Eclipse Distribution License, a weak copyleft rather than a permissive licence.

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.

Eclipse Mosquitto: How many clients can it handle?

A few thousand concurrent connections on ordinary hardware; beyond that, use a clustered broker.

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.

Eclipse Mosquitto: Does it support MQTT 5?

Yes, along with 3.1.1 and 3.1.

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