PG Vector vs Pinecone
Compare deployment options, cost efficiency, and features to choose the right vector database for your application. If you want to compare these models on your data, try Agentset.
Database Comparison
PG Vector takes the lead.
Both PG Vector and Pinecone are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why PG Vector:
- PG Vector ranks higher overall
- PG Vector offers more deployment options
- PG Vector is more cost-effective
- PG Vector has more permissive licensing
- PG Vector has 2 more strengths
Vector Databases Are Just One Piece of RAG
Agentset gives you a managed RAG pipeline with the top-ranked models and best practices baked in. No infrastructure to maintain, no vector database to operate.
Trusted by teams building production RAG applications
PG Vector
PG Vector is a popular Postgres extension that adds vector search capabilities directly inside a traditional relational database. It is ideal for teams that want to keep embeddings, metadata, and application data in one system without operating a separate vector database.
Pinecone
Pinecone is a fully managed, proprietary cloud vector database designed for high-performance RAG pipelines. It abstracts away infrastructure, scaling, replication, and index management. Pinecone is popular among companies building production RAG systems that need predictable latency and fully hosted operations.
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with fully managed vector storage and retrieval. Upload your data, call the API, and get accurate results from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}Feature Comparison
Infrastructure & Technical Details
| Feature | PG Vector | Pinecone |
|---|---|---|
| Deployment | Self-Hosted, Managed Cloud | Managed Cloud |
| Cost | Free (extension), infra cost only | Storage: $0.33/GB/mo; Write Units: $4/million; Read Units: $16/million; Minimum $50/mo |
| License | PostgreSQL | Proprietary |
| Index Types | Flat, IVFFlat, HNSW | Dense (HNSW-like), Sparse |
| Cloud Providers | AWS RDS, Azure Postgres, GCP AlloyDB, Supabase, Timescale | AWS, Azure, GCP |
| Regional Flexibility | high | low |
| Strengths | 9 | 7 |
| Weaknesses | 7 | 7 |