OpenSearch Vector
OpenSearch Vector is an open-source search and analytics suite that enables high-performance vector search for AI applications.
FreeWebDesktopAPIOpen sourceKoreanMultimodal
Visit websiteopensearch.org
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OpenSearch Vector is an open-source search and analytics suite that enables high-performance vector search for AI applications. It supports k-NN search using HNSW and IVF algorithms, making it a core component for RAG architectures. By combining traditional lexical search with vector-based semantic search, it provides superior relevance and scalability for handling billions of embeddings.
Key features
- High-performance k-NN search
- Support for HNSW and IVF algorithms
- Hybrid search (Lexical + Semantic)
- Real-time data indexing
- Scalability to billions of vectors
- Robust security and access control
- SQL and PPL query support
Pricing
Use cases
- Building RAG-based chatbots
- Image and video similarity search
- Recommendation systems
- Anomaly detection and security analysis
Who it is for
Data EngineersAI DevelopersSearch Architects
Integrations
LangChainLlamaIndexAmazon SageMakerHugging Face
Tags
RAG
How we verified this
Company, pricing, and feature details come from the primary sources below and our latest verification pass. When sources disagree, the official source and the most recent check win.
Last verified 08/30/2026Verified sources: 1
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