Towards an architecture for managing big semantic data in real-time

  • Authors:

  • Carlos E. Cuesta;Miguel A. Martínez-Prieto;Javier D. Fernández

  • Affiliations:

  • VorTIC3 Research Group, Dept. of Comp. Languages and Systems II, Rey Juan Carlos University, Madrid, Spain;DataWeb Research, Dept. of Computer Science, University of Valladolid, Segovia & Valladolid, Spain,Dept. of Computer Science, University of Chile, Santiago, Chile;DataWeb Research, Dept. of Computer Science, University of Valladolid, Segovia & Valladolid, Spain,Dept. of Computer Science, University of Chile, Santiago, Chile

  • Venue:
  • ECSA'13 Proceedings of the 7th European conference on Software Architecture
  • Year:
  • 2013

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Abstract

Big Data Management has become a critical task in many application systems, which usually rely on heavyweight batch processes to process large amounts of data. However, batch architectures are not an adequate choice for the design of real-time systems, where expected response times are several orders of magnitude underneath. This paper outlines the foundations for defining an architecture able to deal with such an scenario, fulfilling the specific needs of real-time systems which expose big RDF datasets. Our proposal (Solid) is a tiered architecture which separates the complexities of Big Data management from their real-time data generation and consumption. Big semantic data are stored and indexed in a compressed way following the Rdf/Hdt proposal; while at the same time, real-time requirements are addressed using NoSQL technology. Both are efficient layers, but their approaches are quite different and their combination is not easy. Two additional layers are required to achieve an overall high performance, satisfying real-time needs, and able to work even in a mobile context.