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 Milvus vs Qdrant by community traction (★ 46k vs ★ 34k). Pick Milvus for billion-scale search; pick Qdrant for production RAG.
✓ Live data verified
| Milvus | Qdrant | |
|---|---|---|
| GitHub stars | ★ 46k | ★ 34k |
| Language | Go | Rust |
| Category | Vector databases | Vector databases |
| Best for | billion-scale search | production RAG |
| Repository | milvus-io/milvus | qdrant/qdrant |
Milvus and Qdrant are both credible choices. By community traction, Milvus leads (★ 46k). Pick Milvus for billion-scale search; pick Qdrant for production RAG.
Both are credible vector databases. By community traction Milvus leads (★ 46k). Pick Milvus for billion-scale search; pick Qdrant for production RAG.
Milvus is Cloud-native vector database built for billion-scale similarity search.. Qdrant is High-performance vector search engine with rich filtering, written in Rust for production-scale retrieval..
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.
Milvus is primarily Go; Qdrant is primarily Rust.
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