Milvus
Open-source vector database for similarity search at scale
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
What this product helps you do
Milvus is an open-source vector database maintained under the LF AI & Data Foundation with Zilliz as a major contributor. Milvus Lite supports local Python use, Standalone runs on one machine, and Distributed uses a Kubernetes-native architecture for larger deployments. The software is free; adopters provide and operate the infrastructure, or can evaluate the separately priced managed Zilliz Cloud service.
Problems it solves
- Unstructured data embeddings need purpose-built storage and indexing
- Similarity search over large vector collections is difficult to scale
- Applications need filtering over vector and scalar fields together
- Teams need deployment choices from local prototypes to distributed clusters
Milvus is an Apache-2.0 vector database for organizing and searching embeddings with related scalar data. It is designed for similarity search workloads behind semantic search, recommendation, RAG, and other AI applications.
Milvus Lite supports local Python prototypes, Standalone runs on one machine, and Distributed supports larger Kubernetes deployments. The project is free; infrastructure is separate, and Zilliz offers a managed commercial service.
Information
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Milvus
Open-source vector database for similarity search at scale
Milvus is an Apache-2.0 vector database for organizing and searching embeddings with related scalar data. It is designed for similarity search workloads behind semantic search, recommendation, RAG, and other AI applications.
Milvus Lite supports local Python prototypes, Standalone runs on one machine, and Distributed supports larger Kubernetes deployments. The project is free; infrastructure is separate, and Zilliz offers a managed commercial service.
What this product helps you do
Milvus is an open-source vector database maintained under the LF AI & Data Foundation with Zilliz as a major contributor. Milvus Lite supports local Python use, Standalone runs on one machine, and Distributed uses a Kubernetes-native architecture for larger deployments. The software is free; adopters provide and operate the infrastructure, or can evaluate the separately priced managed Zilliz Cloud service.
Problems it solves
- Unstructured data embeddings need purpose-built storage and indexing
- Similarity search over large vector collections is difficult to scale
- Applications need filtering over vector and scalar fields together
- Teams need deployment choices from local prototypes to distributed clusters
Information
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
Related AI products
Weaviate
Weaviate stores data objects and vector embeddings for semantic and hybrid search, retrieval-augmented generation, and agent workflows, with open-source self-hosting and managed cloud plans.
Qdrant
Qdrant is a Rust-based vector search engine and managed platform for dense, sparse, hybrid, filtered, multivector, and reranked retrieval across cloud, hybrid, private, and self-hosted deployments.
Chroma
Chroma stores documents, embeddings, and metadata and supports dense, sparse, hybrid, full-text, regex, metadata, and multimodal retrieval through an Apache-2.0 project and serverless cloud service.