Milvus vs Qdrant
Milvus vs Qdrant: side-by-side comparison of two vector-database infrastructure systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Milvus | Qdrant | |
|---|---|---|
| Cost tier | free | free |
| $/Mtok input | 0 | 0 |
| $/Mtok output | 0 | 0 |
Where they differ (12)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Milvus | Qdrant | |
|---|---|---|
| Type | Multi-vector + hybrid + GPU | Vector DB + DBSF + RRF |
| Created | 2019-09 | 2020-05 |
| Latest release | v3.0.3 (2026-10-14) | v1.19.2 (2026-10-05) |
| GitHub | milvus-io/milvus — ~46k stars, last commit 2026-10 | qdrant/qdrant — ~34.9k stars, last commit 2026-10 |
| Pricing | free (OSS); managed via Zilliz Cloud (free tier, then usage-based) | Free tier forever (single node, 1 GB RAM / 4 GB disk); Standard usage-based hourly billing; Premium has minimum spend; Hybrid/Private Cloud via sales |
| Funding | $113M total (Zilliz: $43M 2020 + $60M 2022); Zilliz is the commercial entity | $78M total Series B · 2026-03 |
| Backend storage | custom (object-storage backed; etcd metadata; Pulsar/Kafka log) | custom (Rust-built HNSW + RocksDB metadata) |
| Deployment | Both (self-hosted OSS + Zilliz Cloud managed) | Both (self-hosted + managed cloud) — OSS engine; Qdrant Managed Cloud, Hybrid Cloud and Private Cloud |
| API surface | REST, gRPC, SDK: Python, Java, Go, Node.js, C#, Ruby | REST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C# |
| Embedding | multiple supported | BYO |
| Multi-tenancy | Control plane and data plane in separate VPCs/subnets; BYOC option for hard tenant isolation | Hardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gap |
| MCP | yes — official zilliztech/mcp-server-milvus (GitHub) | yes — official qdrant/mcp-server-qdrant (GitHub, Apache-2.0) |
At a glance
| Milvus | Qdrant | |
|---|---|---|
| Section | Vector-database infrastructure | Vector-database infrastructure |
| Tier | T1 | T1 |
| Type | Multi-vector + hybrid + GPU | Vector DB + DBSF + RRF |
| Created | 2019-09 | 2020-05 |
| Latest release | v3.0.3 (2026-10-14) | v1.19.2 (2026-10-05) |
| License | Apache-2.0 | Apache-2.0 |
| GitHub | milvus-io/milvus — ~46k stars, last commit 2026-10 | qdrant/qdrant — ~34.9k stars, last commit 2026-10 |
| Pricing | free (OSS); managed via Zilliz Cloud (free tier, then usage-based) | Free tier forever (single node, 1 GB RAM / 4 GB disk); Standard usage-based hourly billing; Premium has minimum spend; Hybrid/Private Cloud via sales |
| Funding | $113M total (Zilliz: $43M 2020 + $60M 2022); Zilliz is the commercial entity | $78M total Series B · 2026-03 |
| Backend storage | custom (object-storage backed; etcd metadata; Pulsar/Kafka log) | custom (Rust-built HNSW + RocksDB metadata) |
| Deployment | Both (self-hosted OSS + Zilliz Cloud managed) | Both (self-hosted + managed cloud) — OSS engine; Qdrant Managed Cloud, Hybrid Cloud and Private Cloud |
| API surface | REST, gRPC, SDK: Python, Java, Go, Node.js, C#, Ruby | REST, gRPC, SDK: Python, JS/TS, Rust, Go, Java, C# |
| Embedding | multiple supported | BYO |
| Multi-tenancy | Control plane and data plane in separate VPCs/subnets; BYOC option for hard tenant isolation | Hardened unprivileged container per cluster with strict network policies; outbound restricted; paid plans on dedicated resources; Private Cloud option for air-gap |
| MCP | yes — official zilliztech/mcp-server-milvus (GitHub) | yes — official qdrant/mcp-server-qdrant (GitHub, Apache-2.0) |
| A2A | no Google A2A (Agent2Agent) integration documented as of 2026-05. | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | first-class — Prometheus + 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) |
Pros & cons
Milvus
Pros: Largest-scale OSS vector DB — billions of vectors comfortably; CNCF graduate; strong community in China + research labs.
Cons: Operational complexity is high vs Pinecone-managed; documentation can be uneven across language clients.
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.