An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases

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How researchers see this paper

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Efficient Subgraph Matching by Postponing Cartesian Products (2016, methodology): “We evaluate the algorithms on three real graphs, HPRD 1 , Yeast, and Human, which are widely used in existing works [8, 12, 14, 22].”
Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases (2013, methodology): “Although this greedy approach works for some datasets, it has a serious problem in its matching order for other datasets [8].”
GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph (2014, methodology): “For comparison, we have implemented GGQL; a modified version of G RAM I that replaces ISFREQUENTwith a frequency evaluation function based on G RAPHQL [16]; one of the fastest state-of-the-art subgraph isomorphism techniques [21].”
SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation (2024, unknown): “Recent subgraph isomorphism algorithms often follow a filtering-ordering-enumerating paradigm (Lee et al., 2012; Sun and Luo, 2020; Zhang et al., 2024).”