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Firstly, the graph model can be a natural fit for data sets that have hierarchical, complex, or even arbitrary structures. Such structures can be easily encoded into the graph model as edges. This can be more convenient than the relational model, which requires the [[Database normalization|normalization]] of the data set into a set of tables with fixed row types.
Secondly, the graph model enables efficient execution of expensive queries or data analytic functions that need to observe multi-hop relationships among data entities, such as reachability queries, [[Shortest path problem|shortest or cheapest path queries]], or [[centrality]] analysis. There are two graph models in current use: the Resource Description Framework (RDF) model and the Property Graph model. The RDF model has been standardized by W3C in a number of specifications. The Property Graph model, on the other hand, has a multitude of implementations in graph databases, graph algorithms, and graph processing facilities. However, a common, standardized query language for property graphs (like SQL for relational database systems) is missing. GQL is proposed to fill this void."<ref name="39075 GQL NWIP">{{cite web|url=https://isotc.iso.org/livelink/livelink?func=ll&objId=20911483&objAction=Open&viewType=1|title=SC32 WG3 N282 "SC32 N3002 Draft NWIP Form4 Information Technology – Database Languages - GQL"|publisher=ISO|access-date=December 9, 2019}}</ref>}}
==== Official ISO standard ====
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