Advertisement

Big Data 2.0 Processing Systems

A Survey

  • Sherif Sakr
Book

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Sherif Sakr
    Pages 1-13
  3. Sherif Sakr
    Pages 53-73
  4. Sherif Sakr
    Pages 75-89
  5. Sherif Sakr
    Pages 91-95
  6. Back Matter
    Pages 97-102

About this book

Introduction

This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and big data processing scenarios such as the large-scale processing of structured data, graph data and streaming data. Thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems.

After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Lastly, Chapter 6 shares conclusions and an outlook on future research challenges.

Overall, the book offers a valuable reference guide for students, researchers and professionals in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

Keywords

Database Management Systems Hadoop Stream Data Management Graph Databases Cloud Computing Data Analytics Big Data

Authors and affiliations

  • Sherif Sakr
    • 1
  1. 1.The University of New South WalesSydneyAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-38776-5
  • Copyright Information The Author(s) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-38775-8
  • Online ISBN 978-3-319-38776-5
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
Industry Sectors
Pharma
Materials & Steel
Automotive
Chemical Manufacturing
Biotechnology
Finance, Business & Banking
Electronics
IT & Software
Telecommunications
Consumer Packaged Goods
Energy, Utilities & Environment
Aerospace
Engineering