PathDB: A system for evaluating regular path queries
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866913923480944640 |
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| author | García, Roberto Angles, Renzo Rojas, Vicente Ferrada, Sebastián |
| author_facet | García, Roberto Angles, Renzo Rojas, Vicente Ferrada, Sebastián |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01755 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PathDB: A system for evaluating regular path queries García, Roberto Angles, Renzo Rojas, Vicente Ferrada, Sebastián Databases 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. |
| title | PathDB: A system for evaluating regular path queries |
| topic | Databases |
| url | https://arxiv.org/abs/2507.01755 |