apache-airflow-providers-vespa
Provider package apache-airflow-providers-vespa for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This is an official Apache Airflow provider for Vespa integration, actively maintained with no known vulnerabilities. Install friction is low, the license is permissive, and it's production-ready. Install it if you run Airflow and need to orchestrate Vespa operations; otherwise, it has no value.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; Vespa cluster must be accessible from Airflow environment.
- Low install friction with a pure-Python wheel.
- Actively maintained by Apache; last commit 2026-08-14.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions.
last release 2026-06-07 (68 days) · last repo commit 2026-08-14 · 46,491 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 124,202 downloads/mo, #11,879 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-vespa
from airflow.providers.vespa.operators import VespaOperator
from airflow import DAG
with DAG('vespa_dag') as dag:
task = VespaOperator(task_id='vespa_task')- What specific Vespa operations (feed, query, deploy) are supported by the available operators and hooks.
- Whether authentication mechanisms (API keys, certificates) are documented for Vespa cluster connections.
- Performance characteristics when handling large-scale data pipelines to Vespa.
What it is and what it does
This is an Apache Airflow provider package that adds Vespa integration capabilities to Airflow workflows. It allows you to orchestrate tasks that interact with Vespa clusters—a search and machine learning engine—directly from Airflow DAGs. The package provides operators and hooks built on top of pyvespa, the official Python client for Vespa, enabling you to define, schedule, and monitor Vespa operations as part of larger data pipelines.
The package is production-ready (Development Status 5) and actively maintained by the Apache Airflow project. It supports Python 3.10 through 3.14 and requires Airflow >=2.11.0. Installation is straightforward via pip, with low friction since it's a pure-Python wheel with no compiled dependencies.
Use it for
- Schedule regular data feeds to Vespa search clusters as part of an Airflow pipeline.
- Orchestrate machine learning model deployments and updates to Vespa clusters on a fixed schedule.
- Build multi-step workflows that query Vespa, process results, and feed refined data back.
- Monitor and manage Vespa cluster operations (indexing, redeployment) alongside other Airflow tasks.
- Integrate Vespa search operations into larger ETL or data processing DAGs.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is an official Apache Airflow provider for Vespa integration, actively maintained with no known vulnerabilities. Install friction is low, the license is permissive, and it's production-ready. Install it if you run Airflow and need to orchestrate Vespa operations; otherwise, it has no value.
Install
apache-airflow-providers-vespa on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained by Apache; last commit 2026-08-14. Requires Apache Airflow >=2.11.0 and pyvespa >=1.1.2.
Requires Apache Airflow >=2.11.0 and Python >=3.10; Vespa cluster must be accessible from Airflow environment.
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions.
Quickstart
pip install apache-airflow-providers-vespa
from airflow.providers.vespa.operators import VespaOperator
from airflow import DAG
with DAG('vespa_dag') as dag:
task = VespaOperator(task_id='vespa_task')Verify before relying
- What specific Vespa operations (feed, query, deploy) are supported by the available operators and hooks.
- Whether authentication mechanisms (API keys, certificates) are documented for Vespa cluster connections.
- Performance characteristics when handling large-scale data pipelines to Vespa.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesapache-airflowapache-airflow-providers-common-compatpyvespa |
| Maintenance | Actively maintained 68 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 124,202 / month, #11,879 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_vespa-0.1.1-py3-none-any.whl
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See also apache-airflow-providers-openfaas · pyvespa · apache-airflow-providers-zendesk · apache-airflow-providers-asana · apache-airflow-providers-vertica · apache-airflow-providers-segment · apache-airflow-providers-apache-flink · apache-airflow-providers-informatica · apache-airflow-providers-jenkins · apache-airflow-providers-jira