apache-airflow-providers-jdbc
Provider package apache-airflow-providers-jdbc for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you need Airflow to interact with JDBC databases. The package is actively maintained, carries no known vulnerabilities, has low install friction, and is backed by the Apache Airflow project. The main gotcha is jpype1's platform-specific constraints; verify those match your deployment environment before committing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a working Apache Airflow installation (>=2.11.0) and a JDBC driver JAR file accessible to the Java runtime via jpype1; jpype1 has platform-specific version constraints, particularly on Python 3.10 and 3.11 on macOS ARM64.
- Low friction installation as a pure Python wheel.
- Actively maintained with recent releases; requires Apache Airflow >=2.11.0 and jpype1 with platform-specific version constraints (notably excluding jpype1 1.7.0 on certain configurations).
License · maintenance · safety
Apache-2.0 (permissive) — Apache License 2.0 (permissive) allows commercial and private use with minimal restrictions; suitable for most deployment contexts.
last release 2026-06-07 (68 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,768,360 downloads/mo, #3,573 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-jdbc
from airflow.providers.jdbc.operators.jdbc import JdbcOperator
task = JdbcOperator(
task_id='query_task',
jdbc_conn_id='my_jdbc_connection',
sql='SELECT * FROM table'
)- Whether jaydebeapi and jpype1 require system-level Java installation or if bundled JRE is sufficient
- Performance characteristics when executing large result sets or complex queries through the JDBC bridge
- Compatibility matrix with specific JDBC drivers (e.g., PostgreSQL, MySQL, Oracle, SQL Server)
What it is and what it does
This is an Apache Airflow provider package that enables Airflow DAGs to connect to and query JDBC-compatible databases. It bridges Python and Java by wrapping jaydebeapi and jpype1, allowing Airflow tasks to execute SQL operations against any database with a JDBC driver available.
The package is part of Airflow's ecosystem of database providers and integrates with Airflow's connection and operator framework. It supports Python 3.10 through 3.14 and requires Airflow 2.11.0 or later. Installation is straightforward via pip, though jpype1 has platform-specific version constraints that may affect setup on certain configurations, particularly macOS ARM64 systems.
Use it for
- Execute SQL queries against legacy or proprietary databases that only expose JDBC drivers from Airflow DAG tasks
- Orchestrate ETL workflows that need to read from or write to JDBC-connected databases as part of a larger pipeline
- Monitor database health or run periodic maintenance queries through Airflow's scheduling and alerting framework
- Integrate JDBC data sources with Airflow's lineage and metadata tracking via the openlineage optional dependency
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need Airflow to interact with JDBC databases.
The package is actively maintained, carries no known vulnerabilities, has low install friction, and is backed by the Apache Airflow project. The main gotcha is jpype1's platform-specific constraints; verify those match your deployment environment before committing.
Install
apache-airflow-providers-jdbc on PyPI
Before you install
Low friction installation as a pure Python wheel. Actively maintained with recent releases; requires Apache Airflow >=2.11.0 and jpype1 with platform-specific version constraints (notably excluding jpype1 1.7.0 on certain configurations).
Requires a working Apache Airflow installation (>=2.11.0) and a JDBC driver JAR file accessible to the Java runtime via jpype1; jpype1 has platform-specific version constraints, particularly on Python 3.10 and 3.11 on macOS ARM64.
License in practice
Apache License 2.0 (permissive) allows commercial and private use with minimal restrictions; suitable for most deployment contexts.
Quickstart
pip install apache-airflow-providers-jdbc
from airflow.providers.jdbc.operators.jdbc import JdbcOperator
task = JdbcOperator(
task_id='query_task',
jdbc_conn_id='my_jdbc_connection',
sql='SELECT * FROM table'
)Verify before relying
- Whether jaydebeapi and jpype1 require system-level Java installation or if bundled JRE is sufficient
- Performance characteristics when executing large result sets or complex queries through the JDBC bridge
- Compatibility matrix with specific JDBC drivers (e.g., PostgreSQL, MySQL, Oracle, SQL Server)
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesapache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqljaydebeapijpype1 |
| Maintenance | Actively maintained 68 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,768,360 / month, #3,573 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_jdbc-5.5.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “airflow jdbc database provider”
- apache-airflow-providers-jdbcProvides Apache Airflow integration for executing queries and…
- apache-airflow-providers-common-sqlProvides common SQL operators, hooks, and utilities for Apache…
- apache-airflow-providers-sqliteIntegrates SQLite databases with Apache Airflow as a provider…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also apache-airflow-providers-mysql · JayDeBeApi · apache-airflow-providers-common-sql · apache-airflow-providers-oracle · apache-airflow-providers-microsoft-mssql · apache-airflow-providers-odbc · apache-airflow-providers-sqlite · apache-airflow-providers-databricks · apache-airflow-providers-apache-druid · apache-airflow-providers-ydb