A side-by-side of two vector databases for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: Milvus leads Qdrant vs Milvus by community traction (★ 46k vs ★ 34k). Pick Qdrant for production RAG; pick Milvus for billion-scale search.
✓ Live data verified
| Qdrant | Milvus | |
|---|---|---|
| GitHub stars | ★ 34k | ★ 46k |
| Language | Rust | Go |
| Category | Vector databases | Vector databases |
| Best for | production RAG | billion-scale search |
| Repository | qdrant/qdrant | milvus-io/milvus |
Qdrant and Milvus are both credible choices. By community traction, Milvus leads (★ 46k). Pick Qdrant for production RAG; pick Milvus for billion-scale search.
Both are credible vector databases. By community traction Milvus leads (★ 46k). Pick Qdrant for production RAG; pick Milvus for billion-scale search.
Qdrant is High-performance vector search engine with rich filtering, written in Rust for production-scale retrieval.. Milvus is Cloud-native vector database built for billion-scale similarity search..
Milvus has more — ★ 46k vs ★ 34k (live counts).
Often yes — many teams combine vector databases. Check each tool's docs for interop; they solve overlapping but not identical problems.
Qdrant is primarily Rust; Milvus is primarily Go.
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