pgvector vs Qdrant
pgvector vs Qdrant: side-by-side comparison of two vector-database infrastructure systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| pgvector | Qdrant | |
|---|---|---|
| Cost tier | free | free |
| $/Mtok input | 0 | 0 |
| $/Mtok output | 0 | 0 |
Where they differ (14)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| pgvector | Qdrant | |
|---|---|---|
| Type | PostgreSQL vector extension | Vector DB + DBSF + RRF |
| Created | 2021-04 | 2020-05 |
| Latest release | no releases | v1.17.1 2026-03-27 |
| License | Custom | Apache-2.0 |
| GitHub | 21.1k★ +123/mo C | 31.1k★ +156/mo Rust |
| Pricing | Free (PostgreSQL License open source) | Free + paid |
| Funding | No external funding — open-source project by independent developer | $78M total Series B · 2026-03 |
| Backend storage | Postgres | custom (Rust-built HNSW + RocksDB metadata) |
| Deployment | Self-hosted only (PostgreSQL extension; managed via Supabase/AWS RDS/etc.) | Both |
| API surface | SQL via Postgres protocol | REST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C# |
| Multi-tenancy | Logical isolation via Postgres schemas/databases; managed providers (Supabase, Neon, RDS) add tenant-level controls | Hardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gap |
| MCP | via Postgres MCP servers (community) | via official adapter — mcp-server-qdrant |
| A2A | not supported | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | via Postgres OTel | first-class — Prometheus + OTel |
At a glance
| pgvector | Qdrant | |
|---|---|---|
| Section | Vector-database infrastructure | Vector-database infrastructure |
| Tier | T1 | T1 |
| Type | PostgreSQL vector extension | Vector DB + DBSF + RRF |
| Created | 2021-04 | 2020-05 |
| Latest release | no releases | v1.17.1 2026-03-27 |
| License | Custom | Apache-2.0 |
| GitHub | 21.1k★ +123/mo C | 31.1k★ +156/mo Rust |
| Pricing | Free (PostgreSQL License open source) | Free + paid |
| Funding | No external funding — open-source project by independent developer | $78M total Series B · 2026-03 |
| Backend storage | Postgres | custom (Rust-built HNSW + RocksDB metadata) |
| Deployment | Self-hosted only (PostgreSQL extension; managed via Supabase/AWS RDS/etc.) | Both |
| API surface | SQL via Postgres protocol | REST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C# |
| Embedding | BYO | BYO |
| Multi-tenancy | Logical isolation via Postgres schemas/databases; managed providers (Supabase, Neon, RDS) add tenant-level controls | Hardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gap |
| MCP | via Postgres MCP servers (community) | via official adapter — mcp-server-qdrant |
| A2A | not supported | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | via Postgres OTel | first-class — Prometheus + OTel |
| Optimised for | low-latency similarity search + scale | low-latency similarity search + scale |
| Anti-fit | not for relational / graph-heavy queries (vector-first by design) | not for relational / graph-heavy queries (vector-first by design) |
Taxonomy
| Axis | pgvector | Qdrant |
|---|---|---|
| storage | vector | vector |
| retrieval | similarity | similarity |
| persistence | long-term | long-term |
| update | overwrite | overwrite |
| unit | chunk | chunk |
| governance | inspectable | inspectable |
| conflict | overwrite | overwrite |
Pros & cons
pgvector
Pros: Postgres extension — keeps vector data alongside transactional data with full ACID; minimal ops for shops already running Postgres.
Cons: Performance plateau at very large vector counts; limited filter pushdown vs purpose-built engines.
Qdrant
Pros: Rust-built — fastest of the OSS vector DBs in many benchmarks; strong filtering and hybrid search; clean API.
Cons: Smaller managed-cloud presence than Pinecone; ecosystem of integrations still maturing relative to Weaviate.