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Declarative and distributed graph analytics with GRADOOP

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Junghanns, Martin; Kießling, Max; Teichmann, Niklas; Gomez, Kevin; Petermann, Andre; Rahm, Erhard
Declarative and distributed graph analytics with GRADOOP


We demonstrate Gradoop, an open source framework that combines and extends features of graph database systems with the benefits of distributed graph processing. Using a rich graph data model and powerful graph operators, users can declaratively express graph analytical programs for distributed execution without needing advanced programming experience or a deeper understanding of the underlying sys-tem. Visitors of the demo can declare graph analytical pro-grams using the Gradoop operators and also visually expe-rience two of our advanced operators: graph pattern matching and graph grouping. We provide real world and artificial social network data with up to 10 billion edges and allow running the programs either locally or on a remote research cluster to demonstrate scalability.

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