---
id: apache-airflow-providers-apache-iceberg
version: "2.0.3"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# apache-airflow-providers-apache-iceberg — Provider package apache-airflow-providers-apache-iceberg for Apache Airflow

License: permissive · Maintenance: active · Downloads: 1.6M/mo

## What it is and what it does

This is an Apache Airflow provider package that bridges Airflow's orchestration framework with Apache Iceberg, a table format designed for large-scale analytics. It supplies operators and hooks that allow you to define Iceberg-related tasks within Airflow DAGs—for example, creating tables, inserting or updating data, or triggering transformations on Iceberg datasets. The package is maintained as part of the official Airflow ecosystem and depends on pyiceberg for the underlying Iceberg protocol implementation.

You install it alongside an existing Airflow deployment (version 2.11.0 or later) and import its operators into your DAG definitions. It requires Python 3.10 or later and has no known vulnerabilities. The package is actively maintained and positioned for production use, making it suitable for data teams building Airflow-orchestrated analytics pipelines that use Iceberg as their table format.

Use it for:

- Orchestrate Iceberg table creation and schema evolution as part of multi-step data pipeline DAGs
- Schedule recurring data ingestion or transformation jobs that read from or write to Iceberg tables
- Coordinate Iceberg operations across multiple data sources and downstream analytics tools in a single workflow
- Monitor and manage Iceberg table state changes as part of larger data lake orchestration
- Integrate Iceberg workloads with Airflow's scheduling, retry logic, and alerting infrastructure

## Worth the install?

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

Integrates Apache Iceberg table format with Apache Airflow, providing operators and hooks to orchestrate Iceberg data operations within Airflow workflows.

Yes, if you run Apache Airflow and use Apache Iceberg. The package is actively maintained, has low install friction, carries a permissive license, and is backed by the Apache project. Install it when you need to orchestrate Iceberg operations within Airflow workflows; skip it if you don't use Airflow or Iceberg.

## Install

pip install apache-airflow-providers-apache-iceberg
uv add apache-airflow-providers-apache-iceberg
poetry add apache-airflow-providers-apache-iceberg

## Installing apache-airflow-providers-apache-iceberg

Before you install: Low install friction; pure Python wheel with three runtime dependencies. Actively maintained with a recent release (68 days old) and backed by the Apache Airflow project's active repository.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most production environments.

Quickstart:

pip install apache-airflow-providers-apache-iceberg

from airflow.providers.apache.iceberg.operators import IcebergOperator
# Use within an Airflow DAG to orchestrate Iceberg operations

Requires apache-airflow >=2.11.0, apache-airflow-providers-common-compat >=1.8.0, and pyiceberg >=0.8.0; Python 3.10 or later.

Verify before relying:

- What specific Iceberg operations (create, insert, update, delete, merge) the operators support
- Whether the provider includes sensors for monitoring Iceberg table state or job completion
- Performance characteristics when orchestrating large-scale Iceberg workloads

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 1.6M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

airflow iceberg integration, iceberg operators airflow, apache iceberg provider, orchestrate iceberg tables, airflow data lake tasks, iceberg airflow hooks, data pipeline iceberg, airflow-provider, data-orchestration, iceberg

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