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Search mechanisms combining vector similarity with structured metadata filtering.
Distinguishing note: Combines vector search with boolean logic, distinct from pure vector or pure keyword search.
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SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer
Merges vector similarity searches with graph traversal and structured data filters in a single query.