期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2017
卷号：14
期号：5
出版社：IJCSI Press
摘要：Nowadays, with the recent evolution of sensor technologies, wireless communications, powerful mobile devices and other real-time sources, the way to process the high-speed and real-time data stream brings new challenges. These challenges of big data systems are to detect, anticipate and predict information with the finest granularity possible. The problem is that the system relies on batch processing, which can give great insight into what has happened in the past; however, they do not have the capacity to deal with what is happening at the moment, and of course it is crucial to process events as they happen to a real-time preview. Many applications like fraud detection, data analytics, and production inspection need a fast response and processing time since big data system is based on the MapReduce framework that can only process a finite set of data, is not suitable for the processing of data stream and is inappropriate to satisfy the constraints in real time. Hence the need for a real-time data stream processing system, since it is fast and processes the data in a minimal time with low latency. This paper gives a clear comparison among the different systems that exist for real time data stream processing as well as a model that was based on the comparison that was conducted before.
