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Graph database
NoSQL storage system specialized in managing data structures composed of nodes, edges, and properties, optimized for queries on complex relationships.
Property
Key-value attribute associated with a node or edge, allowing storage of metadata and specific characteristics for each graph element.
Graph traversal
Algorithmic operation involving navigation through graph nodes and edges according to specific patterns to discover relationships or calculate metrics.
Cypher
Declarative query language developed by Neo4j, using ASCII-art syntax to describe graph patterns in manipulation and query operations.
Centrality
Metric measuring the relative importance of a node in a network, including degree centrality, betweenness, closeness, and eigenvector for network analysis.
Graph index
Optimized data structure accelerating search and filtering queries on node or edge properties in graph databases.
Path
Ordered sequence of nodes connected by edges in a graph, representing a route or chain of relationships between entities.
Graph analysis
Set of algorithmic techniques applied to graph structures to extract insights, detect patterns, and calculate metrics on relationships.
Graph Property Model
Modeling paradigm where data is represented as entities (nodes) with properties and relationships (edges) between them.
GraphQL
Query language and runtime developed by Facebook, allowing clients to request exactly the needed data through a graph structure.
Graph Storage Engine
Underlying component of graph databases responsible for the efficient physical persistence of graph data structures on disk or in memory.
Graph Native Processing
Processing approach where graph operations are executed directly on the native data structure without intermediate conversion.
Multi-model Graph Database
Database system simultaneously supporting the graph model and other models (document, key-value, relational) in a unified platform.