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Databases · head to head

Apache Airflow vs Snowplow

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Snowplow logo

Snowplow

Business Intelligence

Behavioural data pipeline you run in your own cloud, relicensed away from Apache 2.0 in 2024

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Apache Airflow has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job; Snowplow the core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Snowplow covers Own-cloud deployment.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

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

Attributes where Apache Airflow and Snowplow differ
AttributeApache AirflowSnowplow
Starting priceFreeOn request
Pricing modelOpen source, no licence fee; managed services billed separatelyquote
Free tierYesNo
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, Web, Docker
CategoryDatabasesBusiness Intelligence

Identical on both: 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 Snowplow

  • Own-cloud deployment
  • Schema enforcement
  • Warehouse loading
  • Enrichment
  • Trackers
  • Streaming output
  • Data models
  • Snowplow BDP

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

Snowplow

  • A data team that needs full-fidelity event data in its own warehouse to build attribution or machine learning features rather than to populate dashboardsnot Apache Airflow
  • A regulated business that cannot send behavioural data to a third-party analytics vendor and must keep collection inside its own cloud accountnot Apache Airflow
  • A product organisation tired of silently malformed events, which wants a schema contract enforced at collection timenot Apache Airflow
  • A company modelling customer behaviour across web, mobile and server events that needs them in one consistent structurenot 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

Snowplow

  • The core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • You run the pipeline in your own cloud, which means the infrastructure bill, the on-call rota and the upgrade work are yours, and at high event volume that operational cost frequently exceeds what a hosted product would have charged.
  • Schema enforcement is the main benefit and the main friction, because every new event requires a schema to be authored and versioned, and teams without discipline around that end up blocked on their own governance process.
  • There is no analysis layer: Snowplow delivers data to your warehouse and nothing else, so you still need modelling, a BI tool and the people to run them before anyone sees a number.
  • The licence change fractured the community, spawning an Apache 2.0 fork, which means community contributions and third-party tooling are now split across two codebases with uncertain long-term maintenance.

Pricing, plan by plan

Apache Airflow

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

Snowplow

On request
  • Snowplow BDP$undefined/year
    • Commercial pricing quoted by event volume and deployment
    • Core pipeline components under the Snowplow Limited Use Licence Agreement, not Apache 2.0
    • Trackers, analytics SDKs and Iglu SDKs remain Apache 2.0

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 Snowplow if

  • You need own-cloud deployment.
  • You work on Linux, Web, Docker.
  • You also want schema enforcement.
Snowplow review

Questions people ask

Is Apache Airflow or Snowplow better?
Neither clearly leads. Apache Airflow starts at Free and Snowplow at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Snowplow?
Apache Airflow has a free tier; the other does not. Paid plans start at Free for Apache Airflow and On request for Snowplow.
Does Apache Airflow or Snowplow run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Snowplow runs on Linux, Web, Docker.
Can I use Apache Airflow for free?
Yes. Apache Airflow has a free tier, so you can try it without paying. Snowplow starts at On request.
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 Snowplow is typically brought in for.
What can Apache Airflow do that Snowplow cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Snowplow covers Own-cloud deployment, Schema enforcement, Warehouse loading, Enrichment.

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.

Snowplow: Is Snowplow still open source?

Not in the permissive sense. On 8 January 2024 the core pipeline moved from Apache 2.0 to the Snowplow Limited Use Licence Agreement, with version 1.1 following in December 2024, alongside a community licence based on the Confluent Community Licence. Trackers and analytics SDKs remain Apache 2.0.

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.

Snowplow: Can we still run it for free in production?

Free use of the relicensed core components is materially constrained and commercial use generally requires an agreement. Read the current licence text against your intended use rather than relying on older documentation.

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.

Snowplow: Is there an Apache 2.0 alternative?

Yes, a fork called OpenSnowcat was created in response to the relicensing and continues under Apache 2.0.

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.

Snowplow: What does Snowplow BDP cost?

Not published. It is quoted by event volume and deployment, and your own cloud infrastructure costs are separate and additional.

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