Analysis of systems to process massive data stream

The immense growth of data demands switching from traditional data processing solutions to systems, which can process a continuous stream of real time data. Various applications employ stream processing systems to provide solutions to emerging Big Data problems. Open-source solutions such as Storm, Spark Streaming and S4 are an attempt to answer key stream processing questions. The recent introduction of real time stream processing commercial solutions such as Amazon Kinesis, IBM Infosphere Stream reflects industry requirements. The system and application based challenges to handle massive stream of real time data are an active field of research. In this paper, we present a comparative analysis of the existing state-of-the-art stream processing solutions. We also include various domains which are transforming their business model to benefits from stream processing.