llama-index-vector-stores-milvus
llama-index vector_stores milvus integration
Decision gist · record as of 2026-08-14
Yes, if you are already using LlamaIndex and need a scalable vector store. The low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a safe choice. Install only if you have Milvus available or plan to deploy it; this is a connector, not a standalone vector store.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to <4.0); pymilvus dependency may require a Milvus server instance to be running.
- Low friction install with two runtime dependencies.
- Active maintenance status and recent release cycle (latest 2026-03-12) suggest ongoing support.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal legal friction for most projects.
last release 2026-03-12 (155 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 256,611 downloads/mo, #8,461 on PyPI
Alternatives
Verify before relying
pip install llama-index-vector-stores-milvus
from llama_index.vector_stores.milvus import MilvusVectorStore
from llama_index.core import VectorStoreIndex
vector_store = MilvusVectorStore(collection_name="documents")
index = VectorStoreIndex.from_vector_store(vector_store)- Whether pymilvus requires a running Milvus server instance or can operate standalone
- Performance characteristics and scaling limits for the vector store integration
- Compatibility matrix with specific LlamaIndex versions beyond the core dependency
What it is and what it does
This package provides a connector between LlamaIndex and Milvus, a vector database designed for similarity search and AI workloads. It allows you to store document embeddings in Milvus and retrieve them efficiently for retrieval-augmented generation (RAG) pipelines and semantic search applications. The integration sits on top of llama-index-core and pymilvus, handling the translation between LlamaIndex's vector store interface and Milvus's API.
The package is lightweight and actively maintained, with low installation friction since it only depends on two runtime packages. It targets modern Python versions (3.10+) and is licensed under MIT, making it straightforward to integrate into commercial or open-source projects.
Use it for
- Building RAG systems where document embeddings are stored in Milvus for fast semantic retrieval
- Implementing multi-tenant vector search applications using Milvus collections
- Integrating LlamaIndex-based LLM chains with an existing Milvus deployment
- Prototyping semantic search features that need to scale beyond in-memory vector stores
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using LlamaIndex and need a scalable vector store.
The low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a safe choice. Install only if you have Milvus available or plan to deploy it; this is a connector, not a standalone vector store.
Install
llama-index-vector-stores-milvus on PyPI
Before you install
Low friction install with two runtime dependencies. Active maintenance status and recent release cycle (latest 2026-03-12) suggest ongoing support.
Requires Python 3.10 or later (supports up to <4.0); pymilvus dependency may require a Milvus server instance to be running.
License in practice
MIT license permits unrestricted use, modification, and distribution with minimal legal friction for most projects.
Quickstart
pip install llama-index-vector-stores-milvus
from llama_index.vector_stores.milvus import MilvusVectorStore
from llama_index.core import VectorStoreIndex
vector_store = MilvusVectorStore(collection_name="documents")
index = VectorStoreIndex.from_vector_store(vector_store)Verify before relying
- Whether pymilvus requires a running Milvus server instance or can operate standalone
- Performance characteristics and scaling limits for the vector store integration
- Compatibility matrix with specific LlamaIndex versions beyond the core dependency
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesllama-index-corepymilvus |
| Maintenance | Actively maintained 155 days since the last release |
| First released | |
| Downloads | 256,611 / month, #8,461 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: llama_index_vector_stores_milvus-1.1.0-py3-none-any.whl
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See also llama-index-vector-stores-pinecone · llama-index-vector-stores-qdrant · langchain-milvus · llama-index-vector-stores-chroma · llama-index-vector-stores-redis · llama-index-vector-stores-lancedb · pymilvus.model · llama-index-vector-stores-faiss · milvus-lite · llama-index-vector-stores-postgres