{"ID":2899224,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.01755","arxiv_id":"2507.01755","title":"PathDB: A system for evaluating regular path queries","abstract":"PathDB is a Java-based graph database designed for in-memory data loading and querying. By utilizing Regular Path Queries (RPQ) and a closed path algebra, PathDB processes paths through its three main components: the parser, the logical plan, and the physical plan. This modular design allows for targeted optimizations and modifications without impacting overall functionality. Benchmark experiments illustrate PathDB's execution times and flexibility in handling dynamic and complex path queries, compared to baseline methods like Depth-First Search (DFS) and Breadth-First Search (BFS) guided by an automaton, highlighting PathDB optimizations that contribute to its performance. PathDB was also evaluated against leading commercial graph systems, including Neo4j, Memgraph, and Kùzu. Benchmark experiments demonstrated PathDB competitive execution times and its ability to support a wide range of path query types.","short_abstract":"PathDB is a Java-based graph database designed for in-memory data loading and querying. By utilizing Regular Path Queries (RPQ) and a closed path algebra, PathDB processes paths through its three main components: the parser, the logical plan, and the physical plan. This modular design allows for targeted optimizations...","url_abs":"https://arxiv.org/abs/2507.01755","url_pdf":"https://arxiv.org/pdf/2507.01755v2","authors":"[\"Roberto García\",\"Renzo Angles\",\"Vicente Rojas\",\"Sebastián Ferrada\"]","published":"2025-07-02T14:33:05Z","proceeding":"cs.DB","tasks":"[\"cs.DB\"]","methods":"[]","has_code":false}