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Today, the problem of processing big data in real time is observed not only in unstructured big data but also in dealing with structured data in databases of small businesses and organizations due to the rapid increase in data volume. Traditional methods and approaches are not considered effective to solve the problem. Moreover, most of the modern effective approaches are based on the cooperation of several computers, and they require plenty of expenses, so it is not suitable for small organizations. The approach proposed in this chapter aims to effectively process big data in real time, bypassing the shortcomings above. The proposed approach is based on the use of a distributed computing mechanism on a single server. The chapter reveals the architecture of this approach, the functional scheme, the essence of the approach, and the effectiveness of the approach. Moreover, in the chapter improving the effectiveness of the approach through machine learning is discussed. Experimental results have been obtained based on the approach and they compared with the traditional approach.

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