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Databases · head to head

Apache Airflow vs Refact

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Refact logo

Refact

Developer Tools

Autonomous AI coding agent for development tasks

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; Refact requires configuration for optimal performance
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Refact covers Autonomous agent workflows.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

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

Attributes where Apache Airflow and Refact differ
AttributeApache AirflowRefact
Pricing modelOpen source, no licence fee; managed services billed separatelyFreemium with paid tiers
PlatformsLinux, Docker, Kubernetes, Self-hostedVS Code, Web
CategoryDatabasesDeveloper Tools
FoundedUnknown2023

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 Refact

  • Autonomous agent workflows
  • IDE chat
  • Real-time code completions
  • GitHub integration
  • Database integration
  • On-premise deployment
  • Multi-LLM support
  • 25+ language support

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

Refact

  • Autonomous code generation for development tasksnot Apache Airflow
  • End-to-end bug fixes and refactoringnot Apache Airflow
  • Multi-language software development accelerationnot Apache Airflow
  • Enterprise development with data privacy requirementsnot 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

Refact

  • Requires configuration for optimal performance
  • On-premise deployment adds operational complexity
  • Free tier limited by daily agent request quota
  • Coin system adds complexity to cost calculation

Pricing, plan by plan

Apache Airflow

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

Refact

Free
  • FreeFree
    • Limited daily agent usage
    • Unlimited completions
    • 2,000 coins for agent and chat
  • Pro$10/month
    • 40 daily agent requests
    • 64k context window
    • 10,000 coins monthly
  • Enterprise$undefined/custom
    • On-premise deployment
    • Custom coin allocation
    • Fine-tuning 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 Refact if

  • You need autonomous agent workflows.
  • You want to start without paying.
  • You work on VS Code, Web.
  • You also want ide chat.
Refact review

Questions people ask

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

Refact: How many programming languages does Refact support?

Refact supports 25+ programming languages including Python, JavaScript, Go, Rust, Java, C++, and many others.

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.

Refact: Can I deploy Refact on-premises?

Yes. Refact offers on-premise deployment options for organizations requiring complete data control and privacy.

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.

Refact: What LLMs does Refact support?

Refact works with multiple LLMs including Claude, GPT-4, and open-source models, giving you flexibility in model selection.

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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