Milvus

Zilliz

The open-source vector database built for billion-scale similarity search: cloud-native, GPU-ready, and the engine behind many enterprise RAG stacks that outgrew a laptop store.

Product preview

Overview

Milvus is the vector database you reach for when the collection is no longer a demo: cloud-native components, optional GPU indexes, and a scale-out story that Zilliz will run for you if you do not want to operate etcd and MinIO. It is older than the current RAG boom, which is why enterprises already had it when ChatGPT arrived.

Compared with Qdrant it is heavier and more distributed; compared with Chroma it is not a notebook toy. The cost is operational complexity and a query surface you must learn. For RAG or recall that has to survive a billion vectors, it is on the shortlist with Pinecone and Weaviate.

Pros / Cons

Pros

Proven at billion-vector scale
GPU indexes when CPU ANN is not enough
Open source with a serious Cloud
Older than the RAG tutorial wave

Cons

Heavier to operate than Qdrant
Distributed pieces to understand
Overkill for a notebook RAG

Who it's for

Enterprise RAG at large collection size

Recall systems that outgrew a single node

GPU-accelerated similarity search

Replacing a hosted vector DB for residency

Bottom line

The heavyweight open-source vector database — pick it when the collection has left the laptop.

Key Features

Billion-scale ANN with cloud-native scale-out

GPU index options

Hybrid search and scalar filters

Milvus / Zilliz Cloud

SDKs for Python, Java, Go, Node

Compare Milvus with alternatives

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Frequently asked questions

What is Milvus?

Milvus is a AI Platforms tool developed by Zilliz. The company was founded in 2019 and is headquartered in San Francisco, USA. The open-source vector database built for billion-scale similarity search: cloud-native, GPU-ready, and the engine behind many enterprise RAG stacks that outgrew a laptop store.