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Databases · head to head

Apache Airflow vs Thanos

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Thanos logo

Thanos

Cloud

Highly available Prometheus with long-term object storage

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; Thanos several components — sidecar, store, querier, compactor, ruler — each with its own configuration and failure modes
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Thanos covers Global query.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

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

Attributes where Apache Airflow and Thanos differ
AttributeApache AirflowThanos
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, no licence fee
PlatformsLinux, Docker, Kubernetes, Self-hostedKubernetes, Linux, Docker
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 Thanos

  • Global query
  • Object storage retention
  • Deduplication
  • Downsampling

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

Thanos

  • Querying metrics across many clusters or regions from one placenot Apache Airflow
  • Retaining metrics for years without local disk growthnot Apache Airflow
  • Removing the gap that appears when a single Prometheus instance restartsnot 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

Thanos

  • Several components — sidecar, store, querier, compactor, ruler — each with its own configuration and failure modes
  • The compactor is a common source of operational trouble and must not run twice against the same bucket
  • Query latency over object storage is meaningfully higher than local Prometheus
  • Object storage costs and API request charges become real at high volume

Pricing, plan by plan

Apache Airflow

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

Thanos

Free
  • ThanosFree
    • Full functionality
    • No usage limits
    • Community 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 Thanos if

  • You need global query.
  • You want to start without paying.
  • You work on Kubernetes, Linux, Docker.
  • You also want object storage retention.
Thanos review

Questions people ask

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

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.

Thanos: Is Thanos free?

Yes, open source and CNCF-incubating. Costs are the object storage it uses.

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.

Thanos: Does Thanos replace Prometheus?

No. It runs alongside existing Prometheus servers, adding global query, deduplication and long-term storage.

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.

Thanos: Thanos or VictoriaMetrics?

Thanos layers onto Prometheus using object storage and is the more established multi-cluster answer. VictoriaMetrics is a separate store aiming at lower resource use and fewer moving parts.

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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