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Databases · head to head

Apache Airflow vs Temporal

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Temporal logo

Temporal

Automation Integration

Durable execution platform for fault-tolerant workflows.

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; Temporal cloud pricing scales with action volume, with per-million overage fees ($50 per million initially)

Where they differ

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

Attributes where Apache Airflow and Temporal differ
AttributeApache AirflowTemporal
Pricing modelOpen source, no licence fee; managed services billed separatelyfreemium
PlatformsLinux, Docker, Kubernetes, Self-hostedWeb, API, Self-hosted
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 Temporal

Nothing recorded that Apache Airflow does not also cover.

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

Temporal

  • AI pipeline orchestration and long-running AI workflowsnot Apache Airflow
  • Distributed system workflows requiring state durabilitynot Apache Airflow
  • Complex backend processes with retry requirementsnot Apache Airflow
  • High-volume asynchronous task executionnot Apache Airflow
  • Microservices coordination with guaranteed state consistencynot 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

Temporal

  • Cloud pricing scales with action volume, with per-million overage fees ($50 per million initially)
  • Enterprise customers incur additional storage costs beyond base allocations
  • Self-hosted deployments require operational expertise to deploy and maintain the Temporal Service
  • No native workflow UI builder; workflows must be defined in code
  • Free tier limited to self-hosted option only; no free cloud tier

Pricing, plan by plan

Apache Airflow

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

Temporal

Free
  • Open-sourceFree
    • Self-hosted deployment
    • Full platform functionality
    • Community support
  • Essentials$100/month
    • 1 million actions monthly
    • 1 GB active storage
    • 40 GB retained storage
  • Business$500/month
    • 2.5 million actions monthly
    • 2.5 GB active storage
    • 100 GB retained storage
  • Enterprise$undefined/month
    • 10 million actions monthly
    • 10 GB active storage
    • 400 GB retained storage

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 Temporal if

  • You want to start without paying.
  • You work on Web, API, Self-hosted.
Temporal review

Questions people ask

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

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.

Temporal: What programming languages does Temporal support?

Temporal provides native SDKs for Go, Java, .NET, PHP, Python, Ruby, Rust, and TypeScript.

Source
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.

Temporal: Can I run Temporal on-premises or self-hosted?

Yes. Temporal is available as open-source software under the MIT license, allowing self-hosted deployment. Temporal Cloud is also available as a managed service alternative.

Source
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.

Temporal: What is included in the free tier?

$1,000 in free credits for new users to explore Temporal Cloud. Self-hosted Temporal is available free with full platform functionality.

Source
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.

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