apache-airflow-providers-amazon
Provider package apache-airflow-providers-amazon for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This is a production-stable, actively maintained provider package from Apache with no known vulnerabilities, low install friction, and permissive licensing. Install it if you run Airflow and need to orchestrate AWS workloads. Ensure you have airflow >=2.11.0 and Python 3.10+ first.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires apache-airflow >=2.11.0 and Python 3.10 or later.
- AWS credentials must be configured in Airflow connections.
- Low install friction with a wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache License 2.0 (permissive). You can use, modify, and distribute this package freely in commercial and private projects, provided you include a copy of the license and note any modifications.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,489 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 9,596,449 downloads/mo, #1,522 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-amazon
from airflow.providers.amazon.aws.operators.s3 import S3ListOperator
from airflow import DAG
with DAG('example') as dag:
list_s3 = S3ListOperator(task_id='list', bucket_name='my-bucket')- Whether all 15 runtime dependencies are always required or if some are optional for specific AWS services
- Performance characteristics and scalability limits for large-scale workflow orchestration
- Specific AWS service coverage beyond the documented examples in the description
What it is and what it does
This is an Apache Airflow provider package that extends Airflow's orchestration capabilities to work with AWS services. It supplies operators, hooks, sensors, and utilities for building data pipelines and workflows that interact with services like S3, EC2, Lambda, RDS, Redshift, Athena, and SageMaker. The package is maintained by the Apache Software Foundation and is part of Airflow's official provider ecosystem.
You install it on top of an existing Airflow deployment to gain AWS-native task types and connection management. It depends on boto3 and botocore for AWS API access, plus service-specific libraries like redshift_connector for Redshift and PyAthena for Athena queries. The package supports Python 3.10 through 3.14 and is actively maintained with frequent releases.
Use it for
- Orchestrate data pipelines that read from and write to S3 buckets as part of larger Airflow workflows
- Schedule and monitor AWS Lambda function executions from Airflow DAGs
- Query Redshift data warehouses or run Athena SQL queries as scheduled Airflow tasks
- Manage EC2 instances or trigger SageMaker training jobs from workflow definitions
- Build multi-step ETL workflows that combine AWS services with other data sources via Airflow
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 Apache with no known vulnerabilities, low install friction, and permissive licensing. Install it if you run Airflow and need to orchestrate AWS workloads. Ensure you have airflow >=2.11.0 and Python 3.10+ first.
Install
apache-airflow-providers-amazon on PyPI
Before you install
Low install friction with a wheel distribution. Actively maintained as of 6 days ago with 46489 repository stars. Requires apache-airflow >=2.11.0 and 15 runtime dependencies including boto3, botocore, and service-specific connectors like redshift_connector and PyAthena.
Requires apache-airflow >=2.11.0 and Python 3.10 or later. AWS credentials must be configured in Airflow connections.
License in practice
Apache License 2.0 (permissive). You can use, modify, and distribute this package freely in commercial and private projects, provided you include a copy of the license and note any modifications.
Quickstart
pip install apache-airflow-providers-amazon
from airflow.providers.amazon.aws.operators.s3 import S3ListOperator
from airflow import DAG
with DAG('example') as dag:
list_s3 = S3ListOperator(task_id='list', bucket_name='my-bucket')Verify before relying
- Whether all 15 runtime dependencies are always required or if some are optional for specific AWS services
- Performance characteristics and scalability limits for large-scale workflow orchestration
- Specific AWS service coverage beyond the documented examples in the description
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 15 packagesapache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqlapache-airflow-providers-httpboto3botocoreinflectionwatchtowerjsonpath_ngredshift_connectorasgirefPyAthenajmespathsagemaker-studiomarshmallow |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 9,596,449 / month, #1,522 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_amazon-9.34.0-py3-none-any.whl
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See also apache-airflow-providers-google · apache-airflow-providers-databricks · apache-airflow-providers-microsoft-azure · apache-airflow-providers-apache-hive · apache-airflow-providers-postgres · apache-airflow-providers-common-messaging · apache-airflow-providers-standard · apache-airflow-providers-trino · apache-airflow-providers-oracle · awswrangler