Pinecone vs Qdrant Vector Database Pricing & Sizing 2026
Compare Pinecone Serverless vs Qdrant Cloud and self-hosted vector search. Calculate RAG read/write units, memory indexing, and break-even scales.
| Self-Hosted License | Apache 2.0 (100% Free Open Source) |
| Managed Cloud 1GB Cluster | ~$25.00 / month flat |
| Query Price | Included in cluster compute |
| Memory Optimization | Disk-backed on-disk vector payload |
| Quantization | Scalar & Product Quantization (4x memory cut) |
| Filtering Engine | Payload filter with payload index |
| Single Node Scale | 10M+ 1536-dim vectors on 32GB RAM |
| Self-Hosted License | Proprietary Closed SaaS |
| Managed Serverless Storage | $0.33 / GB-month |
| Read Units (RU) | $0.008 / 1K read units |
| Write Units (WU) | $2.00 / 1M write units |
| Memory Optimization | Tiered storage (S3 + NVMe cache) |
| Quantization | Automatic serverless compression |
| Zero Maintenance | Fully automated serverless scaling |
For startups with sporadic query traffic under 500,000 vectors, Pinecone Serverless is virtually zero-maintenance and charges strictly for consumed read/write units ($0.008/1K reads). However, once a production RAG application scales past 5 million vectors or experiences continuous search QPS, Qdrant's disk-backed vector storage and self-hosting options become 4x to 8x cheaper than Pinecone, as cluster costs remain predictable regardless of query volume.
"r/LocalLLaMA: 'Pinecone Serverless was great for the MVP, but at 8M embeddings and continuous agent search loops, our bill hit $600/mo. We deployed Qdrant on a $40 Hetzner dedicated box and latency dropped by half.'"