Siren Federate: Bridging document, relational, and graph models for exploratory graph analysis

• URL: http://arxiv.org/abs/2504.07815v1
• Date: Thu, 10 Apr 2025 14:52:03 GMT
• Title: Siren Federate: Bridging document, relational, and graph models for exploratory graph analysis
• Authors: Georgeta Bordea, Stephane Campinas, Matteo Catena, Renaud Delbru,
• Abstract summary: Investigative require interactive exploratory analysis on large heterogeneous knowledge graphs.<n>This paper discusses the architecture of Siren Federate, a system that efficiently supports exploratory graph analysis.<n> 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.
• Score: 0.6349764856675643
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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