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Amazon OpenSearch's k-NN plugin enables scalable, efficient vector search using ANN algorithms (IVF, HNSW) directly within a managed OpenSearch cluster. It is directly relevant for building, querying, and scaling vector databases on AWS.
AWS has introduced vector search in several of its managed database services, including OpenSearch, Bedrock, MemoryDB, Neptune, and Amazon Q, making it a comprehensive platform for vector search solutions.
Google Vertex AI offers managed vector search capabilities as part of its AI platform, supporting hybrid and semantic search for text, image, and other embeddings.
Azure AI Search provides vector search capabilities as a managed service, supporting approximate KNN, hybrid search, and integration with other Azure AI tools.
MongoDB is a general-purpose database that now includes vector search capabilities, enabling light vector workloads alongside traditional database functionality. MongoDB Atlas, the managed cloud offering, includes vector search built on Lucene, supporting ANN queries and hybrid search. MongoDB Atlas Search integrates powerful vector search capabilities directly within MongoDB.
Pinecone is a managed vector database service optimized for handling vector embeddings at scale. It provides straightforward APIs and infrastructure management, making it popular for adding vector search capabilities to modern applications.
Zilliz Cloud is a fully managed vector database service powered by Milvus, offering hassle-free deployment, scalability, and high performance for vector search applications.