Databases · head to head
Apache Airflow vs PlanetScale

Apache Airflow
Databases
Programmatically author, schedule and monitor data workflows in Python
- 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; PlanetScale pricing varies significantly across 17+ AWS and GCP regions
- They diverge on capability: Apache Airflow covers Pipelines as Python, PlanetScale covers Database Branching.
Where they differ
Only the attributes on which Apache Airflow and PlanetScale actually diverge.
| Attribute | Apache Airflow | PlanetScale |
|---|---|---|
| Pricing model | Open source, no licence fee; managed services billed separately | usage-based |
| Platforms | Linux, Docker, Kubernetes, Self-hosted | Cloud-hosted (AWS, GCP, Azure) |
| Founded | Unknown | 2018 |
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 Apache Airflow
- Pipelines as Python
- Web UI
- Cloud provider packages
- Jinja templating
- Retries and dependencies
- Extensible operators
Only in PlanetScale
- Database Branching
- Non-blocking Schema Changes
- Insights
- Horizontal Scaling
- Connection Pooling
- Query Caching
- Automatic Backups
- Global Replication
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 PlanetScale
- Coordinating machine learning training and evaluation runsnot PlanetScale
- Orchestrating dbt runs alongside extraction and loadingnot PlanetScale
- Replacing a sprawl of cron jobs with dependencies and visible run historynot PlanetScale
PlanetScale
- MySQL-compatible applications requiring horizontal scalingnot Apache Airflow
- PostgreSQL deployments with custom cluster configurationsnot Apache Airflow
- Multi-region database deployments on AWS or GCPnot Apache Airflow
- Applications requiring transparent sharding via Vitessnot 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
PlanetScale
- Pricing varies significantly across 17+ AWS and GCP regions
- Additional costs for EBS storage beyond base tier, backup storage, and egress
- Dedicated PgBouncer and replicas incur separate charges
- Metal tier pricing increases sharply with larger configurations
Pricing, plan by plan
Apache Airflow
Free- Apache AirflowFree
- Full scheduler and web UI
- All provider packages
- No task or DAG limits
PlanetScale
Free- Postgres EBS Single-Node (ARM64 PS-5)$5/month
- 512 MiB RAM
- Single-node configuration
- EBS storage included
- Postgres EBS HA (ARM64 PS-5)$15/month
- 512 MiB RAM
- 3-node high-availability setup
- 1 primary + 2 replicas
- Postgres Metal (M-10)$50/month
- 1/8 vCPU, 1 GiB RAM
- 3-node HA configuration
- 10 GiB NVMe storage included
- Vitess Non-Metal 3-Node$39/month
- Sharding-capable database
- x86-64 architecture
- 3-node configuration
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 PlanetScale if
- You need database branching.
- You want to start without paying.
- You work on Cloud-hosted (AWS, GCP, Azure).
- You also want non-blocking schema changes.
Questions people ask
- Is Apache Airflow or PlanetScale better?
- Neither clearly leads. Apache Airflow starts at Free and PlanetScale at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Apache Airflow or PlanetScale?
- Apache Airflow starts at Free and PlanetScale at Free.
- Does Apache Airflow or PlanetScale run on more platforms?
- Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. PlanetScale runs on Cloud-hosted (AWS, GCP, Azure).
- 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 PlanetScale is typically brought in for.
- What can Apache Airflow do that PlanetScale cannot?
- Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. PlanetScale covers Database Branching, Non-blocking Schema Changes, Insights, Horizontal Scaling.
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.
PlanetScale: How much does a PlanetScale Postgres database cost per month?
PlanetScale Postgres pricing starts at $5/month for single-node ARM64 configurations with 512 MiB RAM and $15/month for the same specs in high-availability mode with 1 primary and 2 replicas. Metal tier starts at $50/month for M-10 configuration (1/8 vCPU, 1 GiB RAM). Exact pricing depends on cluster size, node architecture (ARM64 vs x86-64), storage configuration, and selected AWS/GCP region.
SourceApache 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.
PlanetScale: Is there a free tier for PlanetScale?
PlanetScale offers a free tier for development and testing workloads. After free tier limits are reached, usage-based pricing applies starting at $5/month for the smallest Postgres single-node configuration, with costs scaling based on cluster size, compute, storage, and additional features like dedicated PgBouncer or replicas.
SourceApache 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.
PlanetScale: What is the difference between PlanetScale ARM64 and x86-64 pricing?
ARM64 instances cost significantly less than x86-64 equivalents. For example, a Postgres EBS HA cluster with 512 MiB RAM costs $15/month on ARM64 but $39/month on x86-64. This pricing difference extends across all cluster sizes, with larger x86-64 configurations reaching up to $5,599/month compared to ARM64 alternatives.
SourceApache 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.
PlanetScale: What is included in a PlanetScale cluster price versus additional costs?
The advertised cluster price covers the base compute and configured storage. Additional charges apply for EBS storage beyond the base allocation, backup storage, data egress, optional dedicated PgBouncer connections, and replicas beyond the base high-availability configuration. Regional pricing varies across 17+ AWS and GCP zones.
SourceRelated pages
More on Apache Airflow
More on PlanetScale
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