Answer-first summary49/100 GEO

Milvus

Open-source vector database at scale.

AI InfrastructureFair citabilityVisit site →

Your Citability Score

49/100
Identity60/100
Evidence45/100
Trust15/100
Freshness50/100
Classification80/100
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  • Evidence: Add: At least one evidence link, Multiple evidence sources, Demo URL.
  • Trust: Add: Contact information, Support URL, Privacy policy, Terms of service.
  • Freshness: Add: Has version number, Launch date provided, Reviewed within 90 days.
  • Classification: Add: At least 2 tags.

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Frequently asked questions

What is Milvus?
Open-source vector database at scale.
What does Milvus do?
Open-source vector database built for billion-scale similarity search with GPU acceleration and hybrid search.
Who is Milvus for?
ML engineers, data engineers, and AI platform teams building vector search and retrieval systems.
Is Milvus verified?
Milvus is listed on CitableHub with a citability score of 49/100, computed from verifiable profile evidence.
Milvus logo

Milvus

Invited

Open-source vector database at scale.

AI InfrastructureCH-VER-967312Listed September 11, 2026
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AI-Extractable Summary
What:Open-source vector database at scale.
For whom:ML engineers, data engineers, and AI platform teams building vector search and retrieval systems
Key outcome:Teams can deploy high-scale vector search and retrieval systems that support low-latency similarity queries over billions of embeddings
Category:AI Infrastructure

Structured for AI systems to extract and cite.

Citability Score

49/100
60
Identity
45
Evidence
15
Trust
50
Freshness
80
Classification
49
Impressions
0
Clicks
0
Likes
0
GQI Earned

Citable Outcome

Teams can deploy high-scale vector search and retrieval systems that support low-latency similarity queries over billions of embeddings.

About

Open-source vector database built for billion-scale similarity search with GPU acceleration and hybrid search.

Target Audience: ML engineers, data engineers, and AI platform teams building vector search and retrieval systems.
Not ideal for: Teams that only need a small in-memory library, a lightweight prototype, or a traditional keyword-only search engine.

What makes it different

  • Open-source vector database purpose-built for large-scale embedding workloads
  • Distributed architecture designed for horizontal scaling and high availability
  • Optimized for low-latency approximate nearest neighbor search at billion-vector scale
  • Supports hybrid search by combining vector similarity with scalar metadata filtering

Tags & Classification

semantic searchretrieval augmented generationrecommendation enginesimage similarity searchanomaly detection
ml engineersdata engineersai platform teamsbackend developers
ecommercehealthcarefinancial servicesmedia and entertainment
Platform: PlatformModel: Open Source

Links & Transparency

Cite this Project

BibTeX
@misc{citablehub_milvus,
  title = {Milvus},
  url = {https://citablehub.com/p/milvus},
  note = {Listed September 11, 2026. CitableHub ID: CH-VER-967312},
  year = {2026}
}
APA
Milvus. (2026). CitableHub Software Index. https://citablehub.com/p/milvus.
MLA
"Milvus." CitableHub, 2026, https://citablehub.com/p/milvus.