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Databases · head to head

Apache Airflow vs QuestDB

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
QuestDB logo

QuestDB

Databases

Fast open source time-series database for high throughput ingestion

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; QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features
  • They diverge on capability: Apache Airflow covers Pipelines as Python, QuestDB covers High Throughput Ingestion.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Airflow and QuestDB differ
AttributeApache AirflowQuestDB
Pricing modelOpen source, no licence fee; managed services billed separatelyopen-source
PlatformsLinux, Docker, Kubernetes, Self-hostedDocker, Kubernetes, Cloud (AWS, Azure, GCP)
FoundedUnknown2014

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 QuestDB

  • High Throughput Ingestion
  • SQL Support
  • Time-series Optimization
  • SIMD Vectorization
  • Column-oriented Storage
  • Built-in Web Console
  • InfluxDB Line Protocol
  • PostgreSQL

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

QuestDB

  • Time-series analytics ingesting up to 20M rows/second from IoT sensors or financial data feedsnot Apache Airflow
  • Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Apache Airflow
  • Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not 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

QuestDB

  • Open-source edition lacks high-availability, distributed architecture, and enterprise security features
  • Enterprise edition pricing not published; requires contacting sales for custom quote
  • Ingestion limit of 20M rows/sec platform-dependent; may not scale to extreme throughput requirements

Pricing, plan by plan

Apache Airflow

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

QuestDB

Free

No published plan breakdown. See the QuestDB review.

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 QuestDB if

  • You need high throughput ingestion.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
  • You also want sql support.
QuestDB review

Questions people ask

Is Apache Airflow or QuestDB better?
Neither clearly leads. Apache Airflow starts at Free and QuestDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or QuestDB?
Apache Airflow starts at Free and QuestDB at Free.
Does Apache Airflow or QuestDB run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
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 QuestDB is typically brought in for.
What can Apache Airflow do that QuestDB cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization.

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.

QuestDB: How much does QuestDB Enterprise cost?

QuestDB does not publish specific pricing for the Enterprise tier. Customers must contact QuestDB via their enterprise contact form to receive a custom quote.

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.

QuestDB: Does QuestDB offer a free version?

Yes, QuestDB Open Source is completely free and recommended for evaluation, prototyping, and pilot projects. Enterprise features, high availability, security, and dedicated support require the paid Enterprise tier.

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.

QuestDB: What deployment options does QuestDB offer?

QuestDB offers open source deployment, Enterprise deployment, and Bring Your Own Cloud (BYOC) deployment. Pricing details for BYOC and Enterprise tiers are not published and require direct contact with sales.

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.

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