Characterizing big data software architectures: a systematic mapping study - Sena, Bruno; Allian, Ana Paula; Nakagawa, Elisa Yumi (Anais do Simpósio Brasileiro de Componentes, Arquiteturas e Reutilização de Software (SBCARS), 2017)
Big data is a broad term for large, dynamic, and complex data sets that have brought great challenges to be addressed by traditional software systems. It has also demanded advanced software architectures (i.e., the big data software architectures) prepared to deal with the continuous expansion of the volume of data as well as to take advantage of new technologies for big data context. However, the main characteristics, basic requirements, and modules and organization of big data architectures are not still widely known. Besides that, no detailed overview about them is available. The main contribution of this paper is to present the state of the art related to big data software architectures; for this, we conducted a Systematic Mapping Study. As results, an essential set of eight requirements for big data architectures was identified, besides a collection of five modules that are fundamental to adequately enable the data flow. We also intend these results can guide architects in the development of software systems for this new challenging scenario of big data management.