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apache-airflow-providers-airbyte

Provider package apache-airflow-providers-airbyte for Apache Airflow

apache-airflow-providers-airbyte v6.0.1 2.5M downloads/30d#3,055 on PyPI46,490
Permissive license Apache-2.0 Active released

What it is and what it does

This is an Apache Airflow provider package that bridges Airflow and Airbyte, enabling you to trigger and monitor Airbyte data synchronization jobs from within Airflow DAGs. It wraps Airbyte's API (via the airbyte-api and httpx libraries) and exposes it as Airflow operators and hooks, so you can treat Airbyte jobs as first-class Airflow tasks alongside your other pipeline steps.

The package is actively maintained by the Apache Airflow project and supports Python 3.10, 3.11, 3.12, 3.13, 3.14. It requires Apache Airflow >=2.11.0, apache-airflow-providers-common-compat >=1.12.0, airbyte-api >=1.0.0,<2.0, and httpx >=0.28.1. Installation is straightforward via pip, with no compiled dependencies or special system requirements beyond a working Airflow environment.

Use it for:

  • Trigger Airbyte sync jobs on a schedule or in response to upstream Airflow tasks.
  • Monitor Airbyte job status and fail Airflow DAGs if a sync encounters errors.
  • Chain Airbyte data ingestion with downstream transformation or analysis tasks in a single workflow.
  • Centralize data pipeline orchestration by managing both Airbyte and non-Airbyte tasks in Airflow.
  • Integrate Airbyte syncs into multi-step ETL workflows with conditional logic and dependencies.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Airbyte data pipelines into Apache Airflow workflows, allowing you to orchestrate and monitor Airbyte jobs as Airflow tasks.

Yes. This is a production-stable, actively maintained provider package from the Apache Airflow project with no known vulnerabilities. Install it if you run Airflow and need to orchestrate Airbyte jobs; the low install friction and permissive license make it a straightforward addition to an existing Airflow setup. Verify that your Airflow version meets the >=2.11.0 requirement and that you have an Airbyte instance to connect to.

Install

apache-airflow-providers-airbyte on PyPI

pip

pip install apache-airflow-providers-airbyte

uv

uv add apache-airflow-providers-airbyte

poetry

poetry add apache-airflow-providers-airbyte

Installing apache-airflow-providers-airbyte

Before you install

Low friction install as a pure-Python wheel. Actively maintained with a recent release and backed by the Apache Airflow project. Requires Apache Airflow >=2.11.0 and Python 3.10–3.14.

License in practice

Apache-2.0 (permissive) allows free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart

pip install apache-airflow-providers-airbyte

from airflow.providers.airbyte.operators.airbyte import AirbyteTriggerSyncJobOperator

task = AirbyteTriggerSyncJobOperator(task_id='sync_job')

Requires an existing Apache Airflow installation (>=2.11.0) and a running Airbyte instance with configured jobs.

Verify before relying

  • What specific Airbyte operators and hooks are available beyond job triggering.
  • Whether the package supports Airbyte Cloud, self-hosted, or both deployment models.
  • How error handling and retry logic integrate with Airflow's native mechanisms.
  • Example job IDs or configuration patterns for typical use cases.

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 4 — apache-airflow, apache-airflow-providers-common-compat, airbyte-api, httpx
Maintenance actively maintained — 6 days since the last release
Last repo commit
First released
Downloads 2,455,007/month — #3,055 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: apache_airflow_providers_airbyte-6.0.1-py3-none-any.whl

Keywords: airflow-provider, airbyte, airflow, integration

Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring

Tags

airflow airbyte integrationorchestrate airbyte jobsairflow provider airbytedata pipeline orchestrationairbyte task operatorairflow data syncetl workflow automation
airflow-providerdata-orchestrationetl-integration

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