This paper focuses on Real-Time Data Warehousing systems, a relevant class of Data Warehouses where the main requirement consists in executing classical data warehousing operations (e.g., loading, aggregation, indexing, OLAP query answering, and so forth) under real-time constraints. This makes classical DW architectures not suitable to this goal, and puts the basis for a novel research area which has tight relationship with emerging Cloud architectures. Inspired by this motivation, in this paper we proposed a novel framework for supporting Real-Time Data Warehousing which makes use of a rewrite/merge approach. We also provide an extensive experimental campaign that confirms the benefits deriving from our framework. © 2014 Springer International Publishing.
CITATION STYLE
Cuzzocrea, A., Ferreira, N., & Furtado, P. (2014). Real-time data warehousing: A rewrite/merge approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8646 LNCS, pp. 78–88). Springer Verlag. https://doi.org/10.1007/978-3-319-10160-6_8
Mendeley helps you to discover research relevant for your work.