apache-airflow-providers-weaviate

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

Integrates Weaviate vector database operations into Apache Airflow workflows, providing operators and hooks to orchestrate data ingestion, querying, and management tasks.

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

pip install apache-airflow-providers-weaviate

uv add apache-airflow-providers-weaviate

poetry add apache-airflow-providers-weaviate

Installing apache-airflow-providers-weaviate

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).

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')

Requires an existing Apache Airflow installation (>=2.11.0) and a running Weaviate instance to connect to.

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

Evidence: apache_airflow_providers_weaviate-3.4.1-py3-none-any.whl

Keywords: airflow-provider, weaviate, airflow, integration

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