Turbopuffer 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
Turbopuffer takes the lead.
Both Turbopuffer and Pinecone are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why Turbopuffer:
- Turbopuffer ranks higher overall
- Turbopuffer offers more deployment options
- Turbopuffer is more cost-effective
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
Turbopuffer
⭐Turbopuffer is a fully managed cloud vector database built around a centroid-optimized SPFresh index. It is designed for extremely low-cost, large-scale storage, leveraging object storage engines like S3, GCS, or Azure Blob.
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 | Turbopuffer | Pinecone |
|---|---|---|
| Deployment | BYOC, Managed Cloud | Managed Cloud |
| Cost | Minimum commitment $64/month | Storage: $0.33/GB/mo; Write Units: $4/million; Read Units: $16/million; Minimum $50/mo |
| License | Proprietary | Proprietary |
| Index Types | SPFresh | Dense (HNSW-like), Sparse |
| Cloud Providers | AWS, GCP, Azure | AWS, Azure, GCP |
| Regional Flexibility | high | low |
| Strengths | 7 | 7 |
| Weaknesses | 7 | 7 |