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Databases · head to head

Apache Airflow vs Tilt

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Tilt logo

Tilt

Developer Tools

Local Kubernetes development loop that rebuilds and live-updates containers on save

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; Tilt docker acquired Tilt in 2022 and the team now splits its time across Compose and Docker Desktop, so feature velocity is modest and the product's long-term priority inside Docker is not guaranteed; treat it as a stable utility, not a growing platform.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Tilt covers Live update.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

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

Attributes where Apache Airflow and Tilt differ
AttributeApache AirflowTilt
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, no licence fee
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, macOS, Windows
CategoryDatabasesDeveloper Tools

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 Tilt

  • Live update
  • Tiltfile as code
  • Unified web UI
  • Selective rebuilds
  • Local and remote clusters
  • Resource dependencies
  • Extensions registry
  • Custom buttons and triggers

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

Tilt

  • A team of ten or more engineers whose application is fifteen microservices on Kubernetes and who currently wait on CI to test a changenot Apache Airflow
  • An organisation onboarding new developers who want a single command that stands up the whole stack from a committed Tiltfilenot Apache Airflow
  • A platform team giving product engineers a consistent local environment against a shared remote development clusternot Apache Airflow
  • A codebase where one repository contains several services and rebuilding all of them on every edit is the main source of lost timenot 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

Tilt

  • Docker acquired Tilt in 2022 and the team now splits its time across Compose and Docker Desktop, so feature velocity is modest and the product's long-term priority inside Docker is not guaranteed; treat it as a stable utility, not a growing platform.
  • The Tiltfile is Starlark, a Python dialect, so non-trivial setups become real programs that need reviewing and maintaining, and the person who wrote yours becomes a single point of failure.
  • Live update only works when the running container can accept synced files and restart the process; compiled languages, distroless images and read-only filesystems often force you back to a full image rebuild, which removes the main benefit.
  • It assumes Kubernetes. If your development target is plain Docker Compose or serverless functions, Tilt adds a cluster you did not need and a layer of abstraction with no payoff.
  • There is no commercial support contract, no SLA and no paid tier, so when a Kubernetes version upgrade breaks something you are dependent on GitHub issues and a Slack channel rather than a vendor you can escalate to.

Pricing, plan by plan

Apache Airflow

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

Tilt

Free
  • TiltFree
    • Apache 2.0 licensed
    • All features, no paid tier
    • Community support via the Kubernetes Slack #tilt channel

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 Tilt if

  • You need live update.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want tiltfile as code.
Tilt review

Questions people ask

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

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.

Tilt: Is Tilt free?

Yes, entirely. It is Apache 2.0 open source with no paid tier and no licence fee.

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.

Tilt: Who owns Tilt now?

Docker, which acquired it in May 2022. It remains open source and the repository is still actively maintained.

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.

Tilt: Do I need a remote cluster?

No. It works against a local cluster such as kind, minikube or Docker Desktop, and also against a shared remote development cluster if your services are too heavy to run locally.

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.

Tilt: How is it different from Skaffold?

Both automate the build-deploy loop. Tilt puts more weight on the live-update path and a multi-service dashboard; Skaffold is more configuration-driven and closer to Google's tooling.

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