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Databases · head to head

Apache Airflow vs PostHog

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
PostHog logo

PostHog

Technology

The single platform to analyze, test, observe, and deploy new features

From
Free
Rated
-

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; PostHog the free tier covers 1M events, 5K web session recordings and 2.5K mobile recordings per month before usage-based billing starts
  • They diverge on capability: Apache Airflow covers Pipelines as Python, PostHog covers Product analytics.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Airflow and PostHog differ
AttributeApache AirflowPostHog
Pricing modelOpen source, no licence fee; managed services billed separatelyusage-based
PlatformsLinux, Docker, Kubernetes, Self-hostedWeb, Ios, Android, Api
CategoryDatabasesTechnology
FoundedUnknown2020

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 PostHog

  • Product analytics
  • Session recording
  • Feature flags
  • A/B testing
  • Heatmaps
  • SQL access
  • Data warehouse
  • Apps platform

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

PostHog

  • Product analyticsnot Apache Airflow
  • Feature experimentationnot Apache Airflow
  • User behavior trackingnot Apache Airflow
  • A/B testingnot Apache Airflow
  • Debug production issuesnot 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

PostHog

  • The free tier covers 1M events, 5K web session recordings and 2.5K mobile recordings per month before usage-based billing starts
  • Accounts without a card on file are limited to 1 project; adding one raises it to 6
  • Data retention is 1 year until a card is added, which extends it to 7 years
  • Support is community-only until the account is on a paid plan
  • Error tracking is capped at 100K exceptions and surveys at 1500 responses per month on the free tier

Pricing, plan by plan

Apache Airflow

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

PostHog

Free
  • FreeFree
    • 1M events/month
    • 5K sessions/month
    • Unlimited users
  • Paid$undefined/month
    • $0.00031/event
    • $0.005/session
    • Advanced permissions
  • Enterprise$undefined/month
    • SAML SSO
    • Advanced security
    • Dedicated 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.

Choose PostHog if

  • You need product analytics.
  • You want to start without paying.
  • You work on Web, Ios, Android, Api.
  • You also want session recording.

Questions people ask

Is Apache Airflow or PostHog better?
Neither clearly leads. Apache Airflow starts at Free and PostHog at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or PostHog?
Apache Airflow starts at Free and PostHog at Free.
Does Apache Airflow or PostHog run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. PostHog runs on Web, Ios, Android, Api.
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 PostHog is typically brought in for.
What can Apache Airflow do that PostHog cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. PostHog covers Product analytics, Session recording, Feature flags, A/B testing.

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.

PostHog: What does PostHog's free tier include per month?

PostHog free tier includes: 1M analytics events, 5K session replays, 1M feature flag requests, 100K error tracking exceptions, 1,500 survey responses, 1M data warehouse rows, 10K data pipeline events, 100K AI observability events, 500 PostHog AI credits, 10K workflow messages, and 10GB log ingestion. Source: https://posthog.com/pricing

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.

PostHog: How much data retention does PostHog provide on paid plans?

PostHog free tier provides 1-year data retention. Pay-as-you-go plans offer 7-year data retention across all projects, enabling longer historical analysis. Source: https://posthog.com/pricing

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.

PostHog: What percentage of PostHog users stay on the free tier?

PostHog states that 97% of companies use PostHog for free, indicating extensive free tier adoption. However, specific per-unit pricing rates for overages on paid plans are not published. Source: https://posthog.com/pricing

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.

PostHog: When does PostHog provide priority support on paid plans?

PostHog provides email or Slack support for accounts exceeding $2,000/month on pay-as-you-go plans. Specific response times and support SLAs are not detailed on their pricing page. Source: https://posthog.com/pricing

Source
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