head to head · open source
Milvus vs Qdrant
Milvus has 46,145 GitHub stars, 4,254 forks, 1,405 open issues and last shipped yesterday. Qdrant has 34,638 stars, 2,680 forks, 704 open issues and last shipped yesterday. Milvus leads on adoption by 33% (46,145 vs 34,638 stars). Milvus is written in Go under Apache-2.0; Qdrant is written in Rust under Apache-2.0. Milvus has attracted 9% as many forks as stars, Qdrant 8%. Qdrant was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (hnsw, image-search), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
← all 8884 open source comparisons
Side by side
| Milvus | Qdrant | |
|---|---|---|
| GitHub stars | ★ 46K | ★ 35K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Go | Rust |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 4.3K | ⑂ 2.7K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Milvus if
- You weight community size — 46K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick Qdrant if
- You want the Qdrant feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and Qdrant fits your workflow better
About Milvus
Milvus is a high performance, cloud native vector database written in Go and C++, designed to power AI applications by efficiently storing, indexing, and searching large scale unstructured data such as text, images, and multi modal embeddings. It implements hardware accelerated approximate nearest neighbor (ANN) search using algorithms like HNSW, FAISS, and DiskANN, and supports both real time streaming updates and batch ingestion. Milvus lives in the GenAI infrastructure ecosystem, serving as the persistent storage and retrieval layer for embedding based workloads including RAG, recommendation, and image search.…
read the full Milvus overview →
About Qdrant
Qdrant is a vector similarity search engine and database built in Rust, designed for production use in AI applications. It stores, manages, and retrieves high dimensional vectors alongside associated metadata (payloads), supporting fast nearest neighbor search with filtering. It solves the problem of efficiently performing semantic or neural based matching at scale—such as finding similar images, recommending content, or powering retrieval augmented generation (RAG)—by replacing slow or inflexible brute force or index based approaches with a purpose built engine optimized for vector operations.…
read the full Qdrant overview →
More in Infrastructure & Operations
Related comparisons
More Databases projects
Compare either of these against the rest of the Databases field.
Frequently asked questions
Is Milvus or Qdrant more popular?
Milvus has 46,145 GitHub stars and Qdrant has 34,638. Milvus has the larger community by that measure.
Are Milvus and Qdrant free?
Both are open source. Milvus is licensed under Apache-2.0 and Qdrant under Apache-2.0. Neither carries a licence fee.
What is the difference between Milvus and Qdrant?
Milvus is written in Go and Qdrant in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Milvus or Qdrant?
Choose Milvus if you want the larger community (46,145 stars) or its Apache-2.0 licence terms. Choose Qdrant if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.