Graph Pattern Matching in GQL and SQL/PGQ
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Abstract (arXiv)
As graph databases become widespread, JTC1 -- the committee in joint charge of information technology standards for the International Organization for Standardization (ISO), and International Electrotechnical Commission (IEC) -- has approved a project to create GQL, a standard property graph query language. This complements a project to extend SQL with a new part, SQL/PGQ, which specifies how to define graph views over an SQL tabular schema, and to run read-only queries against them. Both projects have been assigned to the ISO/IEC JTC1 SC32 working group for Database Languages, WG3, which continues to maintain and enhance SQL as a whole. This common responsibility helps enforce a policy that the identical core of both PGQ and GQL is a graph pattern matching sub-language, here termed GPML. The WG3 design process is also analyzed by an academic working group, part of the Linked Data Benchmark Council (LDBC), whose task is to produce a formal semantics of these graph data languages, which complements their standard specifications. This paper, written by members of WG3 and LDBC, presents the key elements of the GPML of SQL/PGQ and GQL in advance of the publication of these new standards.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Dec 2021.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 1; 2026: 4.
10 papers.
- 2023Construction of Knowledge Graphs: State and Challengescited by 12
- 2023Knowledge Graphs Queryingcited by 5
- 2025GraphRAFT: Retrieval Augmented Fine-Tuning for Knowledge Graphs on Graph Databasescited by 5
- 2024IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defensecited by 1
- 2026AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMScited by 1
- 2022Integrating connection search in graph queriescited by 0
- 2024Graph Neural Networks on Graph Databasescited by 0
- 2026The Equivalence Theorem: First-Class Relationships for Structurally Complete Database Systemscited by 0
- 2026A General Sufficient Condition for Rewriting Horn-ALCHI Atomic Queries into GQLcited by 0
- 2026Hidden relationships in a document-derived property graph: top-k chunk embeddings and inverse-distance weighting over a dynamically evolving ontologycited by 0
- 2026Hidden relationships in a document-derived property graph: top-k chunk embeddings and inverse-distance weighting over a dynamically evolving ontology31 Aug 2026
- 2026AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMS10 Aug 2026
- 2026A General Sufficient Condition for Rewriting Horn-ALCHI Atomic Queries into GQL5 Aug 2026
- 2026The Equivalence Theorem: First-Class Relationships for Structurally Complete Database Systems13 Mar 2026
- 2025GraphRAFT: Retrieval Augmented Fine-Tuning for Knowledge Graphs on Graph Databases7 Apr 2025
- 2024IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense23 Nov 2024
- 2024Graph Neural Networks on Graph Databases18 Nov 2024
- 2023Knowledge Graphs Querying23 May 2023
- 2023Construction of Knowledge Graphs: State and Challenges22 Feb 2023
- 2022Integrating connection search in graph queries9 Aug 2022