Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommend…
---
name: pinecone
description: Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [RAG, Pinecone, Vector Database, Managed Service, Serverless, Hybrid Search, Production, Auto-Scaling, Low Latency, Recommendations]
dependencies: [pinecone-client]
---
# Pinecone - Managed Vector Database
The vector database for production AI applications.
## When to use Pinecone
**Use when:**
- Need managed, serverless vector database
- Production RAG applications
- Auto-scaling required
- Low latency critical (<100ms)
- Don't want to manage infrastructure
- Need hybrid search (dense + sparse vectors)
**Metrics**:… load the full skill through Skill Me