milvus vs qdrant

Common questions

What is the difference between milvus and qdrant?

milvus: High-performance cloud-native vector database. qdrant: High-performance, massive-scale Vector Database and Vector Search Engine. See the comparison table for live GitHub stats and shared categories.

When should I choose milvus over qdrant?

Choose milvus over qdrant when milvus is primarily Go; qdrant is Rust; Pricing: Milvus is open-source under Apache-2.0 license.; Requirements: Min 4 GB RAM; Qdrant is a high-performance vector database that serves similar purposes to Milvus, such as scaling vector search, but they are independent solutions; Tags unique to milvus: anns, cloud-native, diskann, distributed; Use Milvus when you need to perform efficient vector similarity searches specifically leveraging the Approximate Nearest Neighbor (ANN) algorithm.

When should I choose qdrant over milvus?

Choose qdrant over milvus when qdrant is primarily Rust; milvus is Go; Qdrant supports self-hosted deployment along with a cloud option at https://cloud.qdrant.io/; Requirements: - Distributed deployment with sharding and replication is supported.; - No specific minimum RAM requirement provided. Performance and resource use will depend on the scale of embedding collections.; Qdrant is a high-performance vector database that serves similar purposes to Milvus, such as scaling vector search, but they are independent solutions; Tags unique to qdrant: ai-search, embeddings-similarity, hnsw, knn-algorithm; Also covers Data & Retrieval; - When scalability and performance are paramount in handling large-scale embeddings.

When should I avoid milvus?

Avoid Milvus when you need immediate native compatibility with FAISS or similar standalone libraries as it has distinct features tailored to its own ecosystem. Do not use Milvus if your application strictly requires real-time indexing updates and low-latency search operations, since optimizing for ANN search may introduce trade-offs in these areas.

When should I avoid qdrant?

- Avoid if your project requires more traditional relational database features as Qdrant focuses exclusively on vectors. - If minimalistic setup is crucial, since Qdrant's capability for distributed deployment may introduce complexity that is not necessary for smaller-scale applications. - For use cases where non-Rust environments significantly limit the feasibility of integrating external tools.

Is milvus or qdrant more popular on GitHub?

milvus has more GitHub stars (45,402 vs 33,629). Stars measure visibility, not whether either tool fits your constraints.

Are milvus and qdrant open source?

Yes - both are open-source projects on GitHub (milvus: Apache-2.0, qdrant: Apache-2.0).

Where can I find alternatives to milvus or qdrant?

GraphCanon lists graph-backed alternatives at milvus alternatives and qdrant alternatives (milvus markdown twin, qdrant markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, milvus or qdrant?

milvus: Very active. qdrant: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for milvus and qdrant?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: milvus trust report; qdrant trust report.