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Databases · head to head

Amazon Aurora vs Apache Airflow

Amazon Aurora logo

Amazon Aurora

Databases

MySQL and PostgreSQL-compatible relational database built for the cloud

From
Free
Rated
-
Full reviewWebsite
Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • They diverge on capability: Amazon Aurora covers MySQL/PostgreSQL Compatible, Apache Airflow covers Pipelines as Python.

Where they differ

Only the attributes on which Amazon Aurora and Apache Airflow actually diverge.

Attributes where Amazon Aurora and Apache Airflow differ
AttributeAmazon AuroraApache Airflow
Pricing modelusage-basedOpen source, no licence fee; managed services billed separately
PlatformsAWS CloudLinux, Docker, Kubernetes, Self-hosted
Founded2006Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

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 Amazon Aurora

  • MySQL/PostgreSQL Compatible
  • 5x MySQL Performance
  • Auto-scaling Storage
  • Global Database
  • Serverless v2
  • Multi-master
  • Fault Tolerant
  • AWS Lambda

Only in Apache Airflow

  • Pipelines as Python
  • Web UI
  • Cloud provider packages
  • Jinja templating
  • Retries and dependencies
  • Extensible operators

What people use each for

The jobs each tool is most often brought in to do.

Amazon Aurora

  • Transaction processingnot Apache Airflow
  • Data storagenot Apache Airflow
  • Application backendnot Apache Airflow
  • Reportingnot Apache Airflow
  • Data analyticsnot Apache Airflow

Apache Airflow

  • Scheduling nightly ETL where step order and retries matternot Amazon Aurora
  • Coordinating machine learning training and evaluation runsnot Amazon Aurora
  • Orchestrating dbt runs alongside extraction and loadingnot Amazon Aurora
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Amazon Aurora

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Amazon Aurora

  • Aurora requires AWS ecosystem knowledge and integration with other AWS services
  • Pricing can become expensive with high-traffic applications using many read replicas
  • Limited support for non-relational data types compared to NoSQL alternatives

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

Pricing, plan by plan

Amazon Aurora

Free
  • Serverless v2$0.12/hour
    • Auto-scaling
    • Pay per ACU
    • Instant scaling
  • Provisioned$29/month
    • Dedicated instances
    • Predictable performance
    • Reserved capacity

Apache Airflow

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

Which should you pick?

Choose Amazon Aurora if

  • You need mysql/postgresql compatible.
  • You want to start without paying.
  • You work on AWS Cloud.
  • You also want 5x mysql performance.
Amazon Aurora review

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

Questions people ask

Is Amazon Aurora or Apache Airflow better?
Neither clearly leads. Amazon Aurora starts at Free and Apache Airflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Aurora or Apache Airflow?
Amazon Aurora starts at Free and Apache Airflow at Free.
Does Amazon Aurora or Apache Airflow run on more platforms?
Amazon Aurora runs on AWS Cloud. Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted.
Can I use Amazon Aurora for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Aurora best used for?
Amazon Aurora is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what Apache Airflow is typically brought in for.
What can Amazon Aurora do that Apache Airflow cannot?
Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating.

Answered from the vendors’ own pages

Amazon Aurora: Is Amazon Aurora compatible with MySQL and PostgreSQL?

Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.

Source
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.

Amazon Aurora: What uptime SLA does Amazon Aurora provide?

Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.

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.

Amazon Aurora: How much does Amazon Aurora cost?

Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.

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.

Amazon Aurora: Can Amazon Aurora scale automatically?

Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.

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.

Amazon Aurora: How many read replicas does Aurora support?

Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.

Source
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