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Databases · head to head

Apache Airflow vs Terragrunt

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Terragrunt logo

Terragrunt

Cloud

The Open Source IaC Orchestrator Platform Teams Trust

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; Terragrunt additional complexity layer on top of Terraform
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Terragrunt covers Infrastructure orchestration.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

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

Attributes where Apache Airflow and Terragrunt differ
AttributeApache AirflowTerragrunt
Pricing modelOpen source, no licence fee; managed services billed separatelyUnknown
PlatformsLinux, Docker, Kubernetes, Self-hostedAWS, Azure, GCP
CategoryDatabasesCloud

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 Terragrunt

  • Infrastructure orchestration
  • Run Queue
  • DRY configuration
  • Automated hooks
  • Infrastructure catalog
  • Least-privilege access

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

Terragrunt

  • Organizing Terraform code across multiple environmentsnot Apache Airflow
  • Automating infrastructure deployment workflowsnot Apache Airflow
  • Implementing infrastructure as code templates for developer self-servicenot 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

Terragrunt

  • Additional complexity layer on top of Terraform
  • Requires understanding of Terraform concepts
  • Paid tier pricing not clearly published

Pricing, plan by plan

Apache Airflow

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

Terragrunt

Free
  • Open SourceFree
    • Terragrunt CLI - completely free
    • Community support
  • Terragrunt Scale FreeFree
    • Free CI/CD pipeline
    • Unlimited runs and resources
    • For up to 25 infrastructure units
  • Terragrunt Scale Paid$undefined/custom
    • Volume pricing for more than 25 infrastructure units
    • Enterprise support

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 Terragrunt if

  • You need infrastructure orchestration.
  • You want to start without paying.
  • You work on AWS, Azure, GCP.
  • You also want run queue.
Terragrunt review

Questions people ask

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

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.

Terragrunt: Is Terragrunt free?

Yes, the Terragrunt CLI is completely free and open source. Terragrunt Scale offers a free tier for up to 25 infrastructure units.

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.

Terragrunt: What is the difference between Terragrunt and Terraform?

Terragrunt is an orchestration layer on top of Terraform that handles state management, DRY principles, and deployment automation without replacing Terraform itself.

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.

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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