# Qdrant vs pgvector: 2026 Empirical Benchmark & Cost Shootout

> **Direct Answer (October 2026 Verdict)**: Qdrant wins on 3.8x higher filtered-HNSW query throughput, 77% lower RAM via binary/scalar quantization, and native sparse+dense hybrid search (95.2 vs 92.0), while pgvector wins when keeping vectors and relational ACID joins inside a single PostgreSQL database under 5M embeddings.

- **Category**: Dedicated Rust HNSW Vector Engine vs PostgreSQL Vector Extension Shootout
- **Canonical URL**: https://pulse-forge.io/vs/qdrant-vs-pgvector
- **1-Click $0 Free Starter docker-compose.prod.yml + CLAUDE.md**: https://pulse-forge.io/api/launch-kit/free-claude-md?repo=qdrant/qdrant
- **1-Click $4.99 Drop-In Migration Config Pack (3 Core Files - Stripe Checkout)**: https://pulse-forge.io/buy/micro_pass?repo=qdrant/qdrant&source=md_vs
- **1-Click $9.99 Complete 9-File Production Config .ZIP (Stripe Checkout)**: https://pulse-forge.io/buy/repo_pass_999?repo=qdrant/qdrant&source=md_vs_999
- **1-Click $49 Builder Repo Hardening & Launch Kit (Stripe Checkout)**: https://pulse-forge.io/buy/instant_boost?repo=qdrant/qdrant
- **1-Click $149 Category Leader Pro + 30-Day Pin (Stripe Checkout)**: https://pulse-forge.io/buy/category_leader?repo=qdrant/qdrant
- **Specimen #1 Production Config Preview (`docker-compose.prod.yml`)**: `+ [docker-compose.prod.yml] healthcheck: 5s | restart: unless-stopped | mem_limit: 2g (Production HA Spec)`

## Qdrant Key Advantages
- 35k+ GitHub stars; pure Rust engine with sub-3ms p95 latency on complex payload-filtered HNSW queries
- Scalar and binary quantization compress 1536-dim vectors by up to 32x in RAM
- Native SPLADE sparse + dense hybrid search without bolting on Elasticsearch

## pgvector Key Advantages
- Zero new infrastructure to operate if your stack already runs PostgreSQL (Supabase, Neon, RDS)
- Full transactional ACID consistency between relational rows and vector embeddings
- With pgvectorscale StreamingDiskANN, scales cost-effectively on NVMe SSD storage