In the era of big data, an unprecedented amount of data is generated every second. The real time analytics has become a force for transforming organizations which are looking for increasing their consumer base and profit. Therefore, the real time stream processing systems have gained a lot of attention, particularly within social media companies such as Twitter and LinkedIn. To identify the open challenges in the area of stream processing and facilitate future advancements, it is essential to synthesize and categorize current stream processing systems. In this chapter, we propose a taxonomy that characterizes and classifies various stream systems. Based on the taxonomy we present a survey and comparison study of the state-of-the-art open source stream computing platforms. The taxonomy and survey is intended to help researchers by providing insights into capabilities of existing stream platforms and businesses by providing criteria that can be leveraged to identify the most suitable stream processing solution that can be adopted for developing their domain-specific applications.
History
Publication title
Software Architecture for Big Data and the Cloud
Editors
I Mistrik, R Bahsoon, N Ali, M Heisel, B Maxim
Pagination
177-200
ISBN
978-0-12-805467-3
Department/School
School of Information and Communication Technology
Publisher
Morgan Kaufmann
Place of publication
Burlington, United States
Extent
20
Rights statement
Copyright 2017 Elsevier Inc.
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified