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Fast and scalable cloud data management

Gessert, Felix.

Fast and scalable cloud data management

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fast and scalable cloud data managementby Felix Gessert, Wolfram Wingerath, Norbert Ritter.
Author:	Gessert, Felix.
other author:	Wingerath, Wolfram.
Published:	Cham :Springer International Publishing :2020.
Description:	xi, 193 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Cloud computingManagement.
Online resource:	https://doi.org/10.1007/978-3-030-43506-6
ISBN:	9783030435066$q(electronic bk.)

Fast and scalable cloud data management
Gessert, Felix.

Fast and scalable cloud data management[electronic resource] /by Felix Gessert, Wolfram Wingerath, Norbert Ritter. - Cham :Springer International Publishing :2020. - xi, 193 p. :ill., digital ;24 cm.

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.

ISBN: 9783030435066$q(electronic bk.)

Standard No.: 10.1007/978-3-030-43506-6doiSubjects--Topical Terms:

544788
Cloud computing
--Management.

LC Class. No.: QA76.585 / .G477 2020

Dewey Class. No.: 004.6782

Fast and scalable cloud data management
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505 0 $a 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.
520 $a 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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