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Databases · head to head

Apache Airflow vs Quadratic

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Quadratic logo

Quadratic

Spreadsheets

Infinite-canvas spreadsheet that runs Python, SQL and formulas in the same grid

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; Quadratic aI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Quadratic covers Multi-language cells.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Airflow and Quadratic differ
AttributeApache AirflowQuadratic
Pricing modelOpen source, no licence fee; managed services billed separatelyPer user per month
PlatformsLinux, Docker, Kubernetes, Self-hostedWeb, macOS, Windows, Linux
CategoryDatabasesSpreadsheets

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 Quadratic

  • Multi-language cells
  • Infinite canvas
  • Direct database connections
  • AI agent in the sheet
  • WebAssembly engine
  • Python package support

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

Quadratic

  • An analyst who wants a SQL result, a Python transformation and a set of manual assumptions visible in one file instead of three toolsnot Apache Airflow
  • Ad hoc modelling where part of the logic is genuinely code and part is a judgement call typed into a cellnot Apache Airflow
  • Sharing a reproducible analysis with a colleague who will only ever open a spreadsheet, not a notebooknot Apache Airflow
  • Prototyping a data pull against a warehouse before committing it to a scheduled pipelinenot 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

Quadratic

  • AI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.
  • Self-hosting is available only on the Enterprise plan, so an organisation that cannot send data to the vendor cloud has to enter a sales negotiation rather than run a container.
  • Excel and Google Sheets compatibility is partial, so files with heavy conditional formatting, pivot tables or macros do not survive a round trip and have to be rebuilt.
  • The product is young and the connector list is short, covering the main relational databases and two warehouses, so anything else has to be reached through Python code you write and maintain yourself.
  • There is no real mobile editing experience, which matters more than it sounds for a spreadsheet because approvals and quick checks routinely happen on a phone.

Pricing, plan by plan

Apache Airflow

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

Quadratic

Free
  • PersonalFree
    • Limited AI usage
    • Limited files and connections
    • Limited sharing
  • Pro$18/month
    • Billed annually
    • 20 USD of AI credits per month
    • Unlimited files
  • Business$36/month
    • Billed annually
    • 40 USD of AI credits per month
    • Advanced permissions
  • Enterprise$undefined/year
    • Quoted
    • Self-hosting option
    • Custom AI usage

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 Quadratic if

  • You need multi-language cells.
  • You want to start without paying.
  • You work on Web, macOS, Windows, Linux.
  • You also want infinite canvas.
Quadratic review

Questions people ask

Is Apache Airflow or Quadratic better?
Neither clearly leads. Apache Airflow starts at Free and Quadratic at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Quadratic?
Apache Airflow starts at Free and Quadratic at Free.
Does Apache Airflow or Quadratic run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Quadratic runs on Web, macOS, Windows, Linux.
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 Quadratic is typically brought in for.
What can Apache Airflow do that Quadratic cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Quadratic covers Multi-language cells, Infinite canvas, Direct database connections, AI agent in the sheet.

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.

Quadratic: Do I need to know Python to use it?

No, formulas work on their own, but the reason to choose Quadratic over Google Sheets is the code cells, so a team with no Python will not get the value.

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.

Quadratic: What happens when the AI credits run out?

Prompting stops until the next monthly reset or until you move up a plan; the spreadsheet itself keeps working normally.

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.

Quadratic: Can it replace a BI tool?

Not for scheduled distribution or governed metrics. It is for exploratory work by one person or a small team, not for dashboards a hundred people read.

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.

Quadratic: Is my database query sent to the vendor?

Connections run through the vendor service on all plans except Enterprise self-hosting, which is the option to take if that is unacceptable.

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