Siren Federate: Bridging document, relational, and graph models for exploratory graph analysis
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916683810078720 |
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| author | Bordea, Georgeta Campinas, Stephane Catena, Matteo Delbru, Renaud |
| author_facet | Bordea, Georgeta Campinas, Stephane Catena, Matteo Delbru, Renaud |
| contents | Investigative workflows require interactive exploratory analysis on large heterogeneous knowledge graphs. Current databases show limitations in enabling such task. This paper discusses the architecture of Siren Federate, a system that efficiently supports exploratory graph analysis by bridging document-oriented, relational and graph models. Technical contributions include distributed join algorithms, adaptive query planning, query plan folding, semantic caching, and semi-join decomposition for path query. Semi-join decomposition addresses the exponential growth of intermediate results in path-based queries. Experiments show that Siren Federate exhibits low latency and scales well with the amount of data, the number of users, and the number of computing nodes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_07815 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Siren Federate: Bridging document, relational, and graph models for exploratory graph analysis Bordea, Georgeta Campinas, Stephane Catena, Matteo Delbru, Renaud Information Retrieval D.2.11; E.1; H.2.4; H.3.3; H.3.4 Investigative workflows require interactive exploratory analysis on large heterogeneous knowledge graphs. Current databases show limitations in enabling such task. This paper discusses the architecture of Siren Federate, a system that efficiently supports exploratory graph analysis by bridging document-oriented, relational and graph models. Technical contributions include distributed join algorithms, adaptive query planning, query plan folding, semantic caching, and semi-join decomposition for path query. Semi-join decomposition addresses the exponential growth of intermediate results in path-based queries. Experiments show that Siren Federate exhibits low latency and scales well with the amount of data, the number of users, and the number of computing nodes. |
| title | Siren Federate: Bridging document, relational, and graph models for exploratory graph analysis |
| topic | Information Retrieval D.2.11; E.1; H.2.4; H.3.3; H.3.4 |
| url | https://arxiv.org/abs/2504.07815 |