apache-airflow-providers-apache-hive
Provider package apache-airflow-providers-apache-hive for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Airflow and need to orchestrate Hive workloads. The package is actively maintained, carries no known vulnerabilities, installs with low friction, and is licensed permissively. It is a standard Airflow provider with production-stable status. Install it only if Hive integration is part of your data pipeline strategy.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Airflow installation (>=2.11.0) and a running Hive server with a configured Airflow connection.
- Low install friction; distributed as a wheel.
- Requires apache-airflow >=2.11.0 and six runtime dependencies including hmsclient and pyhive.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 (permissive): you can use, modify, and distribute this package freely in commercial and private projects, provided you retain license notices and include a copy of the license.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 385,495 downloads/mo, #7,062 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-apache-hive
from airflow.providers.apache.hive.operators.hive import HiveOperator
from airflow import DAG
with DAG('hive_example') as dag:
hive_task = HiveOperator(
task_id='run_hive_query',
hql='SELECT * FROM my_table LIMIT 10',
hive_cli_conn_id='hive_default'
)- Whether optional cross-provider extras (amazon, mysql, presto, etc.) are commonly needed for typical Hive workflows
- Performance characteristics when executing large Hive queries through Airflow
- Specific Hive metastore compatibility or known limitations with particular Hive versions
What it is and what it does
This is an Apache Airflow provider package that adds Hive support to Airflow workflows. It supplies operators, hooks, and sensors for executing Hive queries, managing Hive tables, and integrating Hive metastore operations into Airflow DAGs. The package wraps pyhive and hmsclient to communicate with Hive servers and the Hive metastore.
You install it on top of an existing Airflow installation (>=2.11.0) to gain the ability to define Hive tasks in your workflows. It requires pandas, jmespath, and the common Airflow provider compatibility layers. Optional extras allow integration with cloud storage (amazon), other databases (mysql, presto, vertica, mssql), and Kerberos authentication (GSSAPI).
Use it for
- Execute Hive SQL queries as tasks within Airflow DAGs for ETL pipelines
- Query and manage Hive tables as part of scheduled data workflows
- Integrate Hive metastore operations into multi-step Airflow orchestrations
- Build data pipelines that move data between Hive and other systems via Airflow
- Monitor and log Hive query execution within Airflow's centralized task tracking
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Airflow and need to orchestrate Hive workloads.
The package is actively maintained, carries no known vulnerabilities, installs with low friction, and is licensed permissively. It is a standard Airflow provider with production-stable status. Install it only if Hive integration is part of your data pipeline strategy.
Install
apache-airflow-providers-apache-hive on PyPI
Before you install
Low install friction; distributed as a wheel. Requires apache-airflow >=2.11.0 and six runtime dependencies including hmsclient and pyhive. Actively maintained with a release 6 days old.
Requires an existing Airflow installation (>=2.11.0) and a running Hive server with a configured Airflow connection.
License in practice
Apache-2.0 (permissive): you can use, modify, and distribute this package freely in commercial and private projects, provided you retain license notices and include a copy of the license.
Quickstart
pip install apache-airflow-providers-apache-hive
from airflow.providers.apache.hive.operators.hive import HiveOperator
from airflow import DAG
with DAG('hive_example') as dag:
hive_task = HiveOperator(
task_id='run_hive_query',
hql='SELECT * FROM my_table LIMIT 10',
hive_cli_conn_id='hive_default'
)Verify before relying
- Whether optional cross-provider extras (amazon, mysql, presto, etc.) are commonly needed for typical Hive workflows
- Performance characteristics when executing large Hive queries through Airflow
- Specific Hive metastore compatibility or known limitations with particular Hive versions
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesapache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqlhmsclientpandaspyhivejmespath |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 385,495 / month, #7,062 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_apache_hive-9.6.1-py3-none-any.whl
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See also apache-airflow-providers-google · apache-airflow-providers-mysql · apache-airflow-providers-exasol · apache-airflow-providers-samba · apache-airflow-providers-apache-druid · apache-airflow-providers-salesforce · apache-airflow-providers-amazon · hive-metastore-client · apache-airflow-providers-vertica · pymetastore