Toward real-time data processing: an advanced approach in big data analytics

Abstract

Nowadays, a huge quantity of data are produced by means of multiple data sources. The existing tools and techniques are not capable of handling such voluminous data produced from a variety of sources. This continuous and varied generation of data requires advanced technologies for processing and storage, which seems to be a big challenge for data scientists. Some research studies are well defined in the area of streaming in big data. Streaming data are the real-time data or data in motion such as stock market data, sensor data, GPS data and twitter data. In stream processing, the data are not stored in databases instead it is processed and analyzed on the fly to get the value as soon as they are generated. There are a number of streaming frameworks proposed till date for big data applications that are used to pile up, evaluate and process the data that are generated and captured continuously. In this chapter, we provide an in-depth summary of various big data streaming approaches like Apache Storm, Apache Hive and Apache Samza. We also presented a comparative study regarding these streaming platforms.