---
id: apache-airflow-providers-odbc
version: "4.12.3"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

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

License: permissive · Maintenance: active · Downloads: 2.0M/mo

## What it is and what it does

This is an Apache Airflow provider package that adds ODBC database support to Airflow workflows. It wraps pyodbc to deliver operators and hooks that let you define Airflow tasks that execute SQL queries against any ODBC-compatible database—SQL Server, PostgreSQL via ODBC, MySQL, and others—on a schedule or as part of a larger DAG. The package integrates with Airflow's connection management and common SQL provider framework, so you configure your ODBC connection once in Airflow and reference it by name in your tasks.

Installation is straightforward: it's a pure Python wheel with low friction, depending only on Apache Airflow, two common Airflow provider packages, and pyodbc itself. The package is actively maintained, supports Python 3.10 through 3.14, and carries no known security vulnerabilities. It's aimed at data engineers and system administrators building scheduled data pipelines that need to read from or write to ODBC databases.

Use it for:

- Schedule daily SQL queries against a corporate SQL Server database and load results into a data warehouse.
- Build a multi-step ETL pipeline where one task extracts data via ODBC and passes it to downstream transformation tasks.
- Monitor database health by running periodic ODBC queries and alerting on anomalies.
- Synchronize data between an ODBC source and a cloud data lake on a fixed schedule.
- Integrate legacy database systems (accessible only via ODBC) into modern Airflow-based data workflows.

## Worth the install?

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

Provides ODBC database connectivity operators and hooks for Apache Airflow workflows, enabling scheduled tasks to query and interact with ODBC-compatible databases.

Yes. This is a stable, actively maintained provider package for a common use case—ODBC database integration in Airflow. Install friction is low, the license is permissive, there are no known vulnerabilities, and it supports current Python versions. Install it if you need to orchestrate ODBC database tasks in Airflow; skip it if you don't use Airflow or don't need ODBC connectivity.

## Install

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

## Installing apache-airflow-providers-odbc

Before you install: Low friction installation as a pure Python wheel. Actively maintained with recent releases; requires Apache Airflow 2.11.0 or later and pyodbc 5.0.0+ (5.2.0+ for Python 3.13+).

License in practice: Apache License 2.0 (permissive) — you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.

Quickstart:

pip install apache-airflow-providers-odbc

from airflow.providers.odbc.operators.odbc import ODBCOperator

task = ODBCOperator(
    task_id='query_odbc_db',
    sql='SELECT * FROM table',
    odbc_conn_id='my_odbc_connection'
)

Requires an existing Apache Airflow installation (2.11.0+) and a system ODBC driver configured for your target database.

Verify before relying:

- Which specific ODBC-compatible databases are officially tested or recommended.
- Whether the package includes connection pooling or retry logic beyond pyodbc's native capabilities.
- Performance characteristics for large result sets or long-running queries.

## Package facts

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

## Tags

airflow odbc database provider, odbc connector for airflow, airflow sql database tasks, schedule odbc queries, airflow database integration, odbc airflow operators, airflow data pipeline odbc, airflow-provider, odbc-integration, data-pipeline

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