Skip to content

References: Graph Query Languages and Pattern Matching

  1. Cypher (query language) - Wikipedia - Traces Cypher's origin at Neo4j, its ASCII-art pattern syntax, and its role in the ISO GQL standard, matching this chapter's worked MATCH/WHERE/RETURN examples.

  2. Extract, Transform, Load - Wikipedia - Describes the three-phase ETL process this chapter uses to explain how healthcare records move from source systems into nodes and edges via bulk import.

  3. Subgraph Isomorphism Problem - Wikipedia - Covers the NP-complete problem of matching a pattern graph onto a larger graph, the formal complexity result this chapter cites to justify why indexing matters for Cypher pattern matching.

  4. Graph Databases (2nd Edition) - Ian Robinson, Jim Webber, and Emil Eifrem - O'Reilly Media - Written by Neo4j's own creators, credited with popularizing the ASCII-art MATCH pattern syntax and property-graph modeling style this chapter's Cypher examples follow directly.

  5. The Data Warehouse ETL Toolkit - Ralph Kimball and Joe Caserta - Wiley - The widely used practical reference for designing extract-transform-load pipelines, the same extract-transform-load sequence this chapter applies to moving a relational Patients table into graph nodes.

  6. Cypher Manual - Neo4j Documentation - The official reference for Neo4j's declarative Cypher language, covering the MATCH, WHERE, WITH, and RETURN clauses this chapter builds its worked queries from.

  7. GQL Standard - GQL Standards Committee - The official resource describing ISO/IEC 39075:2024, the graph query language standard this chapter identifies as unifying Cypher-style pattern matching across vendors.

  8. Creating the GQL Database Language Standard - Neo4j Graph Database & Analytics Blog - Recounts the five-year standardization process that fused Cypher, GSQL, and PGQL into GQL, the vendor-fragmentation history this chapter's query-language timeline summarizes.

  9. GSQL Language Reference - TigerGraph Documentation - Introduces GSQL's schema design, loading, and querying environment, including the accumulator-based aggregation this chapter contrasts with Cypher's WITH...count() approach.

  10. Search-Performance Indexes - Neo4j Cypher Manual - Explains how creating an index changes a query's execution plan from a full label scan to an index seek, the exact optimization this chapter demonstrates with a PROFILE comparison.