apache-airflow-providers-airbyte
Provider package apache-airflow-providers-airbyte for Apache Airflow
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow installation (>=2.11.0) and a running Airbyte instance with configured jobs.
- Low friction install as a pure-Python wheel.
- Actively maintained with a recent release and backed by the Apache Airflow project.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 (permissive) allows free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,455,007 downloads/mo, #3,055 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-airbyte
from airflow.providers.airbyte.operators.airbyte import AirbyteTriggerSyncJobOperator
task = AirbyteTriggerSyncJobOperator(task_id='sync_job')- 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.
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 on it.
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
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.
Requires an existing Apache Airflow installation (>=2.11.0) and a running Airbyte instance with configured jobs.
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')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 packagesapache-airflowapache-airflow-providers-common-compatairbyte-apihttpx |
| 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 |
| Classifiers | 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 |
Evidence: apache_airflow_providers_airbyte-6.0.1-py3-none-any.whl
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See also airbyte-api · apache-airflow-providers-apache-flink · apache-airflow-providers-tableau · apache-airflow-providers-apache-spark · apache-airflow-providers-neo4j · apache-airflow-providers-git · apache-airflow-providers-apache-livy · apache-airflow-providers-jenkins · apache-airflow-providers-microsoft-winrm · airbyte