---
id: apache-airflow-providers-pinecone
version: "2.4.5"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# apache-airflow-providers-pinecone — Provider package apache-airflow-providers-pinecone for Apache Airflow

License: permissive · Maintenance: active · Downloads: 128.4K/mo

## What it is and what it does

This is an Apache Airflow provider package that bridges Airflow's workflow orchestration with Pinecone's vector database. It supplies operators, hooks, and connection types that let you build Airflow DAGs to manage vector embeddings, perform similarity searches, and automate vector data pipelines. The package depends on Apache Airflow >=2.11.0, the Pinecone Python client >=7.0.0, and a compatibility layer for common Airflow provider patterns.

The provider is part of the official Apache Airflow ecosystem and is actively maintained. It supports Python 3.10 through 3.14 and is classified as Production/Stable. Use it when you need to schedule and monitor Pinecone operations as part of a larger data workflow, such as ingesting embeddings into an index on a schedule or querying the index as a step in a multi-stage pipeline.

Use it for:

- Schedule periodic ingestion of vector embeddings into Pinecone indexes as part of a data pipeline DAG.
- Orchestrate multi-step workflows where Pinecone similarity search is one task among many data transformations.
- Automate vector index maintenance tasks (upserts, deletes) on a defined schedule using Airflow's scheduling engine.
- Monitor and log Pinecone operations within Airflow's centralized task tracking and alerting framework.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Integrates Pinecone vector database operations into Apache Airflow workflows, enabling DAG-based orchestration of vector search and data management tasks.

Yes, if you run Apache Airflow and need to integrate Pinecone vector operations into your DAGs. The package is actively maintained, has no known vulnerabilities, carries a permissive Apache-2.0 license, and installs with low friction. Install it only if you have an existing Airflow deployment >=2.11.0 and a Pinecone account; it is not a standalone tool.

## Install

pip install apache-airflow-providers-pinecone
uv add apache-airflow-providers-pinecone
poetry add apache-airflow-providers-pinecone

## Installing apache-airflow-providers-pinecone

Before you install: Low install friction with a pure-Python wheel. Actively maintained as part of the Apache Airflow ecosystem; last commit 2026-08-14. Requires Apache Airflow >=2.11.0, pinecone >=7.0.0, and Python >=3.10.

License in practice: Apache-2.0 permissive license. You may use, modify, and distribute this package freely in commercial and private projects, provided you include a copy of the license and notice of modifications.

Quickstart:

pip install apache-airflow-providers-pinecone

from airflow import DAG
from airflow.providers.pinecone.operators.pinecone import PineconeOperator

with DAG('my_dag') as dag:
    task = PineconeOperator(task_id='pinecone_task')

Requires an existing Apache Airflow >=2.11.0 installation and a Pinecone account with API credentials configured.

Verify before relying:

- What specific Pinecone operations (upsert, query, delete) are exposed as operators or hooks.
- Whether the provider includes sensors for waiting on Pinecone index readiness or query completion.
- How authentication to Pinecone is configured (API key management, connection types).

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 128.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

airflow pinecone integration, vector database airflow provider, pinecone dag orchestration, airflow workflow scheduling, vector search automation, airflow-provider, vector-database, orchestration

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