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Several data-intensive applications take streams of events as a continuous input and internally map events onto a dynamic, graph-based data model which is then used for processing. The differences between event processing, graph computing, as well as batch processing and near-realtime processing yield a number of specific requirements for computing platforms that try to unify theses approaches. By combining an altered actor model, an event-sourced persistence layer, and a vertex-based, asynchronous programming model, we propose a distributed computing platform that supports event-driven, graph-based applications in a single platform. Our Chronograph platform concept enables online and offline computations on event-driven, history-aware graphs and supports different processing models on the evolving graph.

Wed 21 Jun
Times are displayed in time zone: (GMT+02:00) Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

11:00 - 12:30: DEBS Research Papers - Session 2: High Performance and Distribution at Sala d'Actes, Vertex Building
Chair(s): Guido SalvaneschiTU Darmstadt
debs-2017-papers11:00 - 11:25
Ruben MayerUniversity of Stuttgart, Muhammad Adnan TariqUniversity of Stuttgart, Kurt RothermelUniversitaet Stuttgart
debs-2017-papers11:25 - 11:50
Kanat TangwongsanMahidol University International College, Martin HirzelIBM Research, Scott SchneiderIBM Research
debs-2017-papers11:50 - 12:10
Daniel RitterSAP SE, Jonas DannSAP SE, Norman MaySAP SE, Stefanie Rinderle-MaUniversity of Vienna
debs-2017-papers12:10 - 12:30
Benjamin ErbUlm University, Germany , Dominik MeißnerInstitute of Distributed Systems, Ulm University, Jakob PietronUlm University, Frank KarglUlm University