NoSQL for Mere Mortals
1st Edition
Published on 6. April 2015
552 pages
978-0-13-402988-7 (ISBN)
Description
The Easy, Common-Sense Guide to Solving Real Problems with NoSQL
The Mere Mortals (R) tutorials have earned worldwide praise as the clearest, simplest way to master essential database technologies. Now, there's one for today's exciting new NoSQL databases. NoSQL for Mere Mortals guides you through solving real problems with NoSQL and achieving unprecedented scalability, cost efficiency, flexibility, and availability.
Drawing on 20+ years of cutting-edge database experience, Dan Sullivan explains the advantages, use cases, and terminology associated with all four main categories of NoSQL databases: key-value, document, column family, and graph databases. For each, he introduces pragmatic best practices for building high-value applications. Through step-by-step examples, you'll discover how to choose the right database for each task, and use it the right way.
Coverage includes
--Getting started: What NoSQL databases are, how they differ from relational databases, when to use them, and when not to Data management principles and design criteria: Essential knowledge for creating any database solution, NoSQL or relational
--Key-value databases: Gaining more utility from data structures
--Document databases: Schemaless databases, normalization and denormalization, mutable documents, indexing, and design patterns
--Column family databases: Google's BigTable design, table design, indexing, partitioning, and Big Data
Graph databases: Graph/network modeling, design tips, query methods, and traps to avoid
Whether you're a database developer, data modeler, database user, or student, learning NoSQL can open up immense new opportunities. As thousands of database professionals already know, For Mere Mortals is the fastest, easiest route to mastery.
The Mere Mortals (R) tutorials have earned worldwide praise as the clearest, simplest way to master essential database technologies. Now, there's one for today's exciting new NoSQL databases. NoSQL for Mere Mortals guides you through solving real problems with NoSQL and achieving unprecedented scalability, cost efficiency, flexibility, and availability.
Drawing on 20+ years of cutting-edge database experience, Dan Sullivan explains the advantages, use cases, and terminology associated with all four main categories of NoSQL databases: key-value, document, column family, and graph databases. For each, he introduces pragmatic best practices for building high-value applications. Through step-by-step examples, you'll discover how to choose the right database for each task, and use it the right way.
Coverage includes
--Getting started: What NoSQL databases are, how they differ from relational databases, when to use them, and when not to Data management principles and design criteria: Essential knowledge for creating any database solution, NoSQL or relational
--Key-value databases: Gaining more utility from data structures
--Document databases: Schemaless databases, normalization and denormalization, mutable documents, indexing, and design patterns
--Column family databases: Google's BigTable design, table design, indexing, partitioning, and Big Data
Graph databases: Graph/network modeling, design tips, query methods, and traps to avoid
Whether you're a database developer, data modeler, database user, or student, learning NoSQL can open up immense new opportunities. As thousands of database professionals already know, For Mere Mortals is the fastest, easiest route to mastery.
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More details
Series
Edition
1. Auflage
Language
English
Place of publication
Boston
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
File size
12,04 MB
ISBN-13
978-0-13-402988-7 (9780134029887)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Dan Sullivan
NoSQL for Mere Mortals
Book
04/2015
Addison Wesley
€45.79
Article exhausted; check different version
Person
Dan Sullivan is a data architect and data scientist with more than 20 years of experience in business intelligence, machine learning, data mining, text mining, Big Data, data modeling, and application design. Dan's project work has ranged from analyzing complex genomics and proteomics data to designing and implementing numerous database applications. His most recent work has focused on NoSQL database modeling, data analysis, cloud computing, text mining, and data integration in life sciences. Dan has extensive experience in relational database design and works regularly with NoSQL databases. Dan has presented and written extensively on NoSQL, cloud computing, analytics, data warehousing, and business intelligence. He has worked in many industries, including life sciences, financial services, oil and gas, manufacturing, health care, insurance, retail, power systems, telecommunications, pharmaceuticals, and publishing.
Content
Preface xxi
Introduction xxv
PART I: INTRODUCTION 1
Chapter 1 Different Databases for Different Requirements 3
Relational Database Design 4
E-commerce Application 5
Early Database Management Systems 6
Flat File Data Management Systems 7
Organization of Flat File Data Management Systems 7
Random Access of Data 9
Limitations of Flat File Data Management Systems 9
Hierarchical Data Model Systems 12
Organization of Hierarchical Data Management Systems 12
Limitations of Hierarchical Data Management Systems 14
Network Data Management Systems 14
Organization of Network Data Management Systems 15
Limitations of Network Data Management Systems 17
Summary of Early Database Management Systems 17
The Relational Database Revolution 19
Relational Database Management Systems 19
Organization of Relational Database Management Systems 20
Organization of Applications Using Relational Database Management Systems 26
Limitations of Relational Databases 27
Motivations for Not Just/No SQL (NoSQL) Databases 29
Scalability 29
Cost 31
Flexibility 31
Availability 32
Summary 34
Case Study 35
Review Questions 36
References 37
Bibliography 37
Chapter 2 Variety of NoSQL Databases 39
Data Management with Distributed Databases 41
Store Data Persistently 41
Maintain Data Consistency 42
Ensure Data Availability 44
Consistency of Database Transactions 47
Availability and Consistency in Distributed Databases 48
Balancing Response Times, Consistency, and Durability 49
Consistency, Availability, and Partitioning: The CAP Theorem 51
ACID and BASE 54
ACID: Atomicity, Consistency, Isolation, and Durability 54
BASE: Basically Available, Soft State, Eventually Consistent 56
Types of Eventual Consistency 57
Casual Consistency 57
&nbs
Introduction xxv
PART I: INTRODUCTION 1
Chapter 1 Different Databases for Different Requirements 3
Relational Database Design 4
E-commerce Application 5
Early Database Management Systems 6
Flat File Data Management Systems 7
Organization of Flat File Data Management Systems 7
Random Access of Data 9
Limitations of Flat File Data Management Systems 9
Hierarchical Data Model Systems 12
Organization of Hierarchical Data Management Systems 12
Limitations of Hierarchical Data Management Systems 14
Network Data Management Systems 14
Organization of Network Data Management Systems 15
Limitations of Network Data Management Systems 17
Summary of Early Database Management Systems 17
The Relational Database Revolution 19
Relational Database Management Systems 19
Organization of Relational Database Management Systems 20
Organization of Applications Using Relational Database Management Systems 26
Limitations of Relational Databases 27
Motivations for Not Just/No SQL (NoSQL) Databases 29
Scalability 29
Cost 31
Flexibility 31
Availability 32
Summary 34
Case Study 35
Review Questions 36
References 37
Bibliography 37
Chapter 2 Variety of NoSQL Databases 39
Data Management with Distributed Databases 41
Store Data Persistently 41
Maintain Data Consistency 42
Ensure Data Availability 44
Consistency of Database Transactions 47
Availability and Consistency in Distributed Databases 48
Balancing Response Times, Consistency, and Durability 49
Consistency, Availability, and Partitioning: The CAP Theorem 51
ACID and BASE 54
ACID: Atomicity, Consistency, Isolation, and Durability 54
BASE: Basically Available, Soft State, Eventually Consistent 56
Types of Eventual Consistency 57
Casual Consistency 57
&nbs
