  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 the attempts to answer key stream processing questions.
The recent introduction of real time stream processing commercial solutions
such as Amazon Kinesis, IBM Infosphere Stream reflect industry requirements.
The system and application related challenges to handle massive stream of real
time data analytics 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
application domains, which are transforming their business model to benefit
from these large scale stream processing systems.
