Milvus

The High-Performance Vector Database Built for Scale

Freemium

Description

Milvus is an open-source vector database engineered for managing and searching large-scale, high-dimensional vector data efficiently. It provides high-performance similarity search capabilities, making it a foundational tool for various Generative AI applications, machine learning tasks, and deep learning processes that rely on vector embeddings. The system is designed to scale elastically, supporting tens of billions of vectors while maintaining retrieval speed and accuracy through features like its Global Index.

Offering flexibility, Milvus provides multiple deployment options to suit different needs: Milvus Lite for learning and prototyping within notebooks or laptops via a simple pip install, Milvus Standalone for robust single-machine production or testing environments handling millions of vectors, and Milvus Distributed for highly reliable, enterprise-grade solutions requiring horizontal scaling for billions of vectors. It integrates smoothly with popular AI development frameworks such as LangChain, LlamaIndex, OpenAI, and Hugging Face, simplifying the development pipeline for applications like RAG, image search, and multimodal search.

Key Features

High-Performance Vector Search: Execute high-speed similarity searches on massive vector datasets.
Scalability: Scale elastically to handle tens of billions of vectors with minimal performance degradation.
Multiple Deployment Options: Offers Milvus Lite, Standalone, and Distributed versions for different scales and use cases.
AI Dev Tool Integration: Compatible with LangChain, LlamaIndex, OpenAI, Hugging Face, DSPy, Haystack, Ragas, MemGPT.
Metadata Filtering: Refine searches based on metadata associated with vectors.
Hybrid Search: Combine vector similarity search with traditional keyword-based search.
Multi-vector Support: Manage multiple vectors associated with a single entity.
Global Index: Ensures fast and accurate data retrieval irrespective of the dataset scale.