Fast & Scalable Cloud Data Management

 
 
Springer (Verlag)
  • erscheint ca. am 15. Juni 2020
 
  • Buch
  • |
  • Hardcover
  • |
  • X, 190 Seiten
978-3-030-43505-9 (ISBN)
 

The unprecedented scale at which data is both produced and consumed today has generated a large demand for scalable data management solutions facilitating fast access from all over the world. As one consequence, a plethora of non-relational, distributed NoSQL database systems have risen in recent years and today's data management system landscape has thus become somewhat hard to overlook. As another consequence, complex polyglot designs and elaborate schemes for data distribution and delivery have become the norm for building applications that connect users and organizations across the globe - but choosing the right combination of systems for a given use case has become increasingly difficult as well.

To help practitioners stay on top of that challenge, this book presents a comprehensive overview and classification of the current system landscape in cloud data management as well as a survey of the state-of-the-art approaches for efficient data distribution and delivery to end-user devices. The topics covered thus range from NoSQL storage systems and polyglot architectures (backend) over distributed transactions and Web caching (network) to data access and rendering performance in the client (end-user).

By distinguishing popular data management systems by data model, consistency guarantees, and other dimensions of interest, this book provides an abstract framework for reasoning about the overall design space and the individual positions claimed by each of the systems therein. Building on this classification, this book further presents an application-driven decision guidance tool that breaks the process of choosing a set of viable system candidates for a given application scenario down into a straightforward decision tree.


1st ed. 2020
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
  • 10
  • |
  • 5 s/w Abbildungen, 10 farbige Abbildungen
  • |
  • 10 Illustrations, color; 5 Illustrations, black and white; X, 190 p. 15 illus., 10 illus. in color.
  • Höhe: 23.5 cm
  • |
  • Breite: 15.5 cm
978-3-030-43505-9 (9783030435059)
weitere Ausgaben werden ermittelt
Felix Gessert is the CEO and co-founder of the Backend-as-a-Service company Baqend. During his PhD studies at the University of Hamburg, he developed the core technology behind Baqend's web performance service. Felix is passionate about making the web faster by turning research results into real-world applications. He frequently talks at conferences about exciting technology trends in data management and web performance. As a Junior Fellow of the German Informatics Society (GI), he is working on new ideas to facilitate the research transfer of academic computer science innovation into practice.
Wolfram "Wolle" Wingerath is the leading data engineer at Baqend where he is responsible for data analytics and all things related to real-time query processing. During his PhD studies at the University of Hamburg, Wolle conceived the scalable design behind Baqend's real-time query engine and thereby also developed a strong background in real-time databases and related technology such as scalable stream processing,NoSQL database systems, cloud computing, and Big Data analytics. Eager to connect with others and share his experiences, Wolle regularly speaks at developer and research conferences.
Norbert Ritter is a full professor of computer science at the University of Hamburg, where he heads the databases and information systems group (DBIS). He received his PhD from the University of Kaiserslautern in 1997. His research interests include distributed and federated database systems, transaction processing, caching, cloud data management, information integration, and autonomous database systems. He has been teaching NoSQL topics in various courses for several years. Seeing the many open challenges for NoSQL systems, he, Wolle, and Felix have been organizing the annual Scalable Cloud Data Management Workshop to promote research in this area.
Preface.- 1 Introduction.- 2 Latency in Cloud-Based Applications.- 3 HTTP for Globally Distributed Applications.- 4 Systems for Scalable Data Management.- 5 Caching in Research & Industry.- 6 Transactional Semantics.-7 Polyglot Persistence in Data Management.- 8 The NoSQL Toolbox: The NoSQL Landscape in a Nutshell.- 9 Summary & Future Trends.
The unprecedented scale at which data is both produced and consumed today has generated a large demand for scalable data management solutions facilitating fast access from all over the world. As one consequence, a plethora of non-relational, distributed NoSQL database systems have risen in recent years and today's data management system landscape has thus become somewhat hard to overlook. As another consequence, complex polyglot designs and elaborate schemes for data distribution and delivery have become the norm for building applications that connect users and organizations across the globe - but choosing the right combination of systems for a given use case has become increasingly difficult as well.

To help practitioners stay on top of that challenge, this book presents a comprehensive overview and classification of the current system landscape in cloud data management as well as a survey of the state-of-the-art approaches for efficient data distribution and delivery to end-user devices. The topics covered thus range from NoSQL storage systems and polyglot architectures (backend) over distributed transactions and Web caching (network) to data access and rendering performance in the client (end-user).

By distinguishing popular data management systems by data model, consistency guarantees, and other dimensions of interest, this book provides an abstract framework for reasoning about the overall design space and the individual positions claimed by each of the systems therein. Building on this classification, this book further presents an application-driven decision guidance tool that breaks the process of choosing a set of viable system candidates for a given application scenario down into a straightforward decision tree.
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