A Four-Layer Architecture for Online and Historical Big Data Analytics

Big data processing and analytics technologies have drawn much attention in recent years. However, the recent explosive growth of online data streams brings new challenges to the existing technologies. These online data streams tend to be massive, continuously arriving, heterogeneous, time-varying and unbounded. Therefore, it is necessary to have an integrated approach to process both big static data and online big data streams. We call this integrated approach online and historical big data analytics (OHBDA). We propose a four-layer architecture of OHBDA, i.e. including the storage layer, online and historical data processing layer, analytics layer, and decision-making layer. Functionalities and challenges of the four layers are further discussed. We conclude with a discussion of the requirements for the future OHBDA solutions, which may serve as a foundation for future big data analytics research.