Unverified50% confidenceFactExact time
Vector search is one of the query capabilities supported by Cosmos DB, used to find the semantically most similar results in vectorized data; Cosmos DB stores vectors in an array property of the document and provides the VectorDistance function to compute distance in queries.
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50%
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Long-term
Relevance
10/22/2026
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Related Claims
UnverifiedSearch systems typically use an embedding model to encode queries and documents into vectors separately and then retrieve candidate results via vector similarity; this process is called semantic retrieval or vector retrieval.68% similarUnverifiedVector search is a technique that encodes unstructured data such as text and images into high-dimensional vectors (embeddings), then uses approximate nearest neighbor (ANN) algorithms to retrieve semantically similar items; common implementations include FAISS, Milvus, Pinecone and pgvector.67% similarUnverifiedVector search works by embedding text into a high-dimensional space and using similarity measures to find the segments closest to the query.67% similarVerifiedVector retrieval relies on vector databases for fuzzy matching and cannot precisely express structural relationships, whereas graph retrieval uses graph databases as the storage medium and is specifically optimized for multi-hop traversal queries.67% similar
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