Graphquery

Graphquery is a term used to describe query languages and interfaces designed to retrieve and manipulate data stored in graph structures. It covers languages that operate on graph databases, knowledge graphs, and other graph-based data stores. Graphqueries focus on nodes, edges, and their properties, enabling users to express patterns and traversals over connected data.

Data models: The two common graph data models are property graphs, where nodes and edges can have key-value properties, and RDF graphs, where data is expressed as triples with subjects, predicates, and objects.

Core capabilities: pattern matching and subgraph queries to find structural motifs; path expressions and traversals; filtering with predicates; path length constraints; aggregation and grouping; projection of variables; ordering and limiting results.

Syntax and execution: Graphquery languages tend to be declarative, letting the engine optimize a query plan. Variables are bound to graph elements; directions of edges are specified; optional matches and unions allow complex queries. Some languages support recursive or transitive closure for arbitrary-length paths.

Relationship to other languages: Graphquery is not a single standard; real-world systems implement graph querying via variants such as Cypher (Neo4j), Gremlin (Apache TinkerPop), and SPARQL (RDF). The term is often used as a generic umbrella for graph query capabilities.

Applications and performance: used in social networks, knowledge graphs, recommendation engines, fraud detection, network topology analysis. Performance depends on indexing, graph modeling, and optimization of query plans.