# Milvus: what AI models say (September 2026)

Source: Memetik Index, https://www.memetik.ai/vendors/milvus
Website: https://www.ibm.com

Milvus was named in 45 of 50 AI answers across 1 category. Best position: Vector databases, 90% answer share, ranked #5, named first in 0%.

## What Milvus is

Milvus is an open-source vector database developed by Zilliz. It is built for organisations managing embedding vectors for AI and machine learning applications, including teams that need to store and search large collections of vectors alongside metadata.

Milvus stores vector embeddings at scale and supports high-performance similarity searches across vector data. It separates storage from compute, allowing each layer to scale independently and horizontally. Embeddings can be ingested with metadata through streaming or batch uploads.

Founded: 2017
(From Milvus's own website, read 2026-09-02.)

## By category

| Category | Rank | Answer share | Named first | Models |
|---|---|---|---|---|
| Vector databases (https://www.memetik.ai/index/vector-databases) | #5 of 16 | 90% | 0% | GPT-5.6 Sol, ChatGPT, GPT-5.6 Luna, Claude Opus 5, Claude, Claude Fable 5, Gemini, Gemini 3.5 Flash, Perplexity, Sonar Reasoning Pro |

## What the models said

> "Choose Milvus if you expect very large-scale open-source vector search and are comfortable with more operational complexity."
> — Perplexity, Vector databases

> "Choose Milvus at genuinely large scale Milvus is worth considering for very large collections, high ingestion rates, or distributed deployments."
> — GPT-5.6 Luna, Vector databases

> "The best vector databases for RAG are Chroma and pgvector for small-scale projects, Qdrant and Milvus for self-hosted production, and Pinecone for fully managed deployments."
> — Claude, Vector databases

> "Milvus / Zilliz: strongest large-scale architecture Milvus spans three operational modes: embedded Milvus Lite, single-machine Standalone, and Kubernetes-oriented Distributed."
> — GPT-5.6 Sol, Vector databases