Streaming Big Data Analytics- Current Status, Challenges and Connection of unbounded data Processing platforms

A strategy of examining immense dimensions of structured, un-structured, Semi-Structured data sets is referred as Big data Analytics. Streaming Big Data refers to data generated continuously from number of data sources like Internet-of-Things (IoT) devices, mobile applications, Embedded Sensors, web clicks and many more are needed to be store, processed and analyzed in a tiny interval of time in order to extract meaningful insights and take proper decisions in a timely fashion as the necessity arises. However analyzing streaming big data (continuous flow or unbounded data) is a very challenging problem. Continuous data streams have become essential prerequisite for numerous industrial and scientific applications, the current existing technology Hadoop-MapReduce is not appropriate for stream processing of big data. This paper discusses the challenges and benefits of streaming big data along with its architecture, and focuses on different open source streaming processing platforms that are existed to process the huge data at a high speed