apache-airflow-providers-weaviate
Provider package apache-airflow-providers-weaviate for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This is a production-stable Apache-backed provider with low install friction, active maintenance, no security vulnerabilities, and a permissive license. Install it if you are already running Airflow and need to orchestrate Weaviate tasks; skip it if you do not use Airflow or do not need vector database integration.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow installation (>=2.11.0) and a running Weaviate instance to connect to.
- Low friction installation as a pure-Python wheel.
- Actively maintained with a release 6 days old and backed by the Apache Airflow project's infrastructure.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 license permits commercial and private use with permissive terms. Derivative works must retain the license notice and copyright attribution.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 287,798 downloads/mo, #8,025 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-weaviate
from airflow.providers.weaviate.operators.weaviate import WeaviateIngestOperator
from airflow import DAG
with DAG('weaviate_example') as dag:
ingest = WeaviateIngestOperator(task_id='ingest_data')- What specific operators and hooks are available beyond the ingest functionality mentioned in the snippet.
- Whether the provider supports all Weaviate client features or a subset of the weaviate-client API.
- Performance characteristics or scaling limits for large-scale data ingestion workflows.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow's workflow orchestration with Weaviate, a vector database platform. It supplies operators, hooks, and connection types that allow you to define Weaviate tasks within Airflow DAGs—such as ingesting data, querying vectors, or managing collections. The package depends on apache-airflow (>=2.11.0), weaviate-client (>=4.16.0, excluding 4.16.7), httpx, pandas, and apache-airflow-providers-common-compat, and runs on Python 3.10 through 3.14.
You install it on top of an existing Airflow setup and use it to compose Weaviate operations into larger data pipelines. It is actively maintained by the Apache Airflow project, with a recent release and no known security vulnerabilities. The permissive Apache-2.0 license places no restrictions on commercial use.
Use it for
- Orchestrate periodic ingestion of document embeddings into Weaviate from external data sources within an Airflow DAG.
- Build multi-step pipelines that extract, transform, and load vector data into Weaviate as part of a larger workflow.
- Query Weaviate collections on a schedule and feed results into downstream Airflow tasks for further processing.
- Manage Weaviate schema and collection lifecycle operations as scheduled Airflow tasks.
- Integrate Weaviate operations with other Airflow providers to create end-to-end ML or search infrastructure workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a production-stable Apache-backed provider with low install friction, active maintenance, no security vulnerabilities, and a permissive license. Install it if you are already running Airflow and need to orchestrate Weaviate tasks; skip it if you do not use Airflow or do not need vector database integration.
Install
apache-airflow-providers-weaviate on PyPI
Before you install
Low friction installation as a pure-Python wheel. Actively maintained with a release 6 days old and backed by the Apache Airflow project's infrastructure. Requires Apache Airflow >=2.11.0 and weaviate-client >=4.16.0 (excluding 4.16.7).
Requires an existing Apache Airflow installation (>=2.11.0) and a running Weaviate instance to connect to.
License in practice
Apache-2.0 license permits commercial and private use with permissive terms. Derivative works must retain the license notice and copyright attribution.
Quickstart
pip install apache-airflow-providers-weaviate
from airflow.providers.weaviate.operators.weaviate import WeaviateIngestOperator
from airflow import DAG
with DAG('weaviate_example') as dag:
ingest = WeaviateIngestOperator(task_id='ingest_data')Verify before relying
- What specific operators and hooks are available beyond the ingest functionality mentioned in the snippet.
- Whether the provider supports all Weaviate client features or a subset of the weaviate-client API.
- Performance characteristics or scaling limits for large-scale data ingestion workflows.
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-compathttpxweaviate-clientpandas |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 287,798 / month, #8,025 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_weaviate-3.4.1-py3-none-any.whl
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See also apache-airflow-providers-salesforce · apache-airflow-providers-neo4j · weaviate-client · apache-airflow-providers-arangodb · apache-airflow-providers-exasol · apache-airflow-providers-opensearch · apache-airflow-providers-github · apache-airflow-providers-oracle · apache-airflow-providers-standard · apache-airflow-providers-postgres