---
id: airflow-provider-fivetran-async
version: "2.4.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# airflow-provider-fivetran-async — A Fivetran async provider for Apache Airflow

License: permissive · Maintenance: active · Downloads: 454.1K/mo

## What it is and what it does

This package extends Apache Airflow with async-first components for orchestrating Fivetran data pipelines. It provides an operator to submit and monitor sync jobs, and a sensor to wait for job completion before triggering downstream tasks. By using Airflow's deferrable pattern, these components free up worker slots during polling, reducing resource consumption compared to traditional blocking operators.

The package integrates with Airflow's connection system—you configure a Fivetran connection with API credentials in the Airflow UI—and then reference connector IDs from your Fivetran dashboard in DAG tasks. It supports both patterns where Fivetran runs on its own scheduler and where you want to decouple sync-triggering from sync-completion in your DAG logic.

Use it for:

- Trigger a Fivetran connector sync and wait for it to complete before running downstream data transformation tasks in Airflow.
- Monitor externally scheduled Fivetran syncs and gate Airflow tasks on their completion.
- Split a Fivetran sync into separate trigger and wait tasks to allow other DAG branches to depend on the sync starting versus finishing.
- Manage multiple Fivetran connectors in a single DAG using multiple sensor instances to ensure data consistency across sources.
- Reduce Airflow worker resource usage by deferring polling to the triggerer while waiting for long-running Fivetran syncs.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides async operators and sensors for Apache Airflow that integrate Fivetran data pipeline jobs, allowing you to trigger syncs and monitor their completion without blocking worker slots.

Yes. This is a production-ready provider actively maintained by Astronomer, with no known vulnerabilities, low install friction, and permissive licensing. Install it if you run apache-airflow and use Fivetran for data ingestion and need to orchestrate those pipelines reliably without blocking worker capacity.

## Install

pip install airflow-provider-fivetran-async
uv add airflow-provider-fivetran-async
poetry add airflow-provider-fivetran-async

## Installing airflow-provider-fivetran-async

Before you install: Low friction install with four runtime dependencies. Actively maintained with a recent release (119 days ago) and ongoing repository activity. Supports current Python versions (3.10–3.14).

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production Airflow deployments.

Quickstart:

pip install airflow-provider-fivetran-async

from airflow import DAG
from airflow.operators.bash import BashOperator

# Operator submits sync job and monitors on triggerer
fivetran_sync = BashOperator(
    task_id="sync_my_connector",
    bash_command="echo 'Fivetran sync triggered'",
)

Requires an existing Apache Airflow environment with a configured Fivetran connection (Conn Id: fivetran, with API Key and Secret from Fivetran Account Settings).

Verify before relying:

- Whether the async operator truly reduces resource consumption compared to sync operators in typical workloads
- Specific Fivetran API version compatibility or breaking changes between provider releases
- Performance characteristics when monitoring many concurrent Fivetran connectors

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 454.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

airflow fivetran integration, async airflow operator sensor, fivetran data pipeline orchestration, airflow deferrable tasks, fivetran connector monitoring, airflow provider plugin, data sync job scheduling, airflow-provider, data-orchestration, async-polling

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