Milvus vs Qdrant
Vector Databases pricing comparison · 2026
Milvus pricing ranges from $0–$155/month, while Qdrant ranges from $0–$0/month. Qdrant is typically 100% more affordable, though your actual cost depends on tier and team size.
Milvus and Qdrant are both open-source vector databases with strong self-hosted communities and managed cloud options, but they differ meaningfully in architecture, feature scope, and target audience. Milvus, originally built at Zilliz and donated to LF AI & Data, is designed for enterprise-scale vector search with support for billions of vectors, distributed deployments, and a rich ecosystem of index types (IVF, HNSW, DiskANN, etc.). Qdrant is a newer, Rust-based vector database focused on performance, payload filtering, and developer ergonomics.
Milvus is the more feature-complete option for large-scale deployments — it supports multiple vector fields per collection, scalar filtering, time-travel (data versioning), and a mature Python/Go/Java SDK ecosystem. However, this power comes with operational complexity; Milvus requires Kubernetes or Docker Compose with multiple dependent services (etcd, MinIO, Pulsar). Qdrant, by contrast, ships as a single binary with no external dependencies, making it far easier to operate.
On pricing, both are free as open-source projects. Qdrant Cloud starts free and remains open-source with no paid tier requirements for self-hosted use. Milvus's managed cloud (Zilliz Cloud) starts free but scales to $1,000/mo or more for larger clusters, reflecting its enterprise focus.
Plan-by-Plan Pricing
| Plan | Milvus | Qdrant |
|---|---|---|
| Open Source (Self-Hosted) | Free /month | Free /month |
| Zilliz Cloud Free | Free /month | Custom |
| Zilliz Cloud Standard | $99 /month | Custom |
| Zilliz Cloud Enterprise | $155 /month | Custom |
| Zilliz Cloud Business Critical | Custom | — |
Our Verdict
Choose Milvus if you're building a large-scale, enterprise AI application that needs to handle billions of vectors, requires advanced index types, or needs multi-vector-field support and data versioning. It's best for teams with DevOps capacity to manage a distributed system or those using Zilliz Cloud for managed hosting.
Choose Qdrant if you want a high-performance, easy-to-operate vector database with excellent payload filtering and a modern Rust-based architecture. It's ideal for teams that prioritize operational simplicity, fast query performance, and a self-hosted deployment that runs as a single binary.
Frequently Asked Questions
01 Is Qdrant free compared to Milvus?
Both Milvus and Qdrant are fully open-source and free to self-host. Qdrant Cloud (managed) starts free with a generous free tier. Milvus's managed cloud (Zilliz Cloud) also has a free tier but paid tiers scale up to $1,000/mo or more for large clusters. For self-hosted deployments, both have zero licensing cost.
02 Which is easier to deploy and operate?
Qdrant is significantly easier to operate. It ships as a single Rust binary with no external service dependencies, making it trivial to run in Docker or on a bare server. Milvus requires orchestrating multiple components (etcd, MinIO, and optionally Pulsar/Kafka) which adds meaningful operational overhead, especially without Kubernetes expertise.
03 Can Qdrant handle the same scale as Milvus?
For most workloads (up to hundreds of millions of vectors), Qdrant performs excellently and is competitive with Milvus. However, Milvus is specifically engineered for billion-scale deployments with distributed sharding, making it the better choice for the very largest AI applications. Teams expecting billion-vector scale from day one should evaluate Milvus or Zilliz Cloud.