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SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data ManagementAugust 2019
Publisher:
  • Springer Vieweg
ISBN:978-3-658-24548-1
Published:29 August 2019
Pages:
248
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Abstract

This book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types: SQL and NoSQL databases, and their respective management systems The nature and uses of Big Data A high-level view of the organization of data management Data Modeling and Consistency Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more. A full chapter probes the challenges of Ensuring Data Consistency, covering: Multi-User Operation Troubleshooting Consistency in Massive Distributed Data Comparison of the ACID and BASE consistency models, and more System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics. Post-Relational and NoSQL Databases The chapter on post-relational databases discusses the limits of SQL – and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases. A final chapter covers NoSQL Databases, along with Development of Non-Relational Technologies, Key-Value, Column-Family and Document Stores XML Databases and Graphic Databases, and more The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.

Cited By

    Contributors
    • University of Fribourg
    • Lucerne University of Applied Sciences and Arts

    Recommendations

    Jaroslav Pokorny

    The book attempts to present an overview of the current state of the art of database technology, that is, mainly data models, database languages, and database architectures, including approaches to ensuring data consistency. Separate chapters are devoted to postrelational and NoSQL databases. Unfortunately, its approach is very unsystematic: some important topics are presented in great detail, some in less, and some not at all. Chapter 1 provides a very informal introduction to the relational data model, structured query language (SQL), big data, and NoSQL databases. Rather unusually, graph databases and the Cypher query language are briefly presented in the last category. Chapter 2 is devoted to data modeling, particularly to the entity-relational (ER) model, relational data model, and graph model, with some rules for implementing the ER schema in relational and graph environments. Unfortunately, a lot of not-too-relevant notions from graph theory are presented here. On the other hand, a conceptual schema is not defined at all; instead, the ER model is used. Chapter 3 describes relational algebra and SQL. While relational algebra is described in detail, only basic language options for SQL are provided. The query by example (QBE) language and some constructs of Cypher are covered, along with short sections about NULL values, integrity constraints, and so on. Chapter 4, "Ensuring Data Consistency," discusses parallel processing in centralized and distributed database management system (DBMS) architectures. Transaction processing, including its ACID and BASE properties, is described in sufficient detail. Chapter 5 discusses some details of a DBMS architecture. The reader finally learns more about the SQL database schema here. In this context, semistructured and unstructured data are recommended for database storage and processing. The chapter includes short sections devoted to data indexing, query optimization, and parallel processing with MapReduce. Finally, it presents the well-known five-layer model for relational databases and various storage structures. Chapter 6 is "Postrelational Databases"; clearly, object-relational and temporal databases belong here, but federated databases belong in chapter 5. The last chapter (7) is so short that it is surprising its title ("NoSQL databases") appears in the title of the entire book. In conclusion, the book can be recommended to anybody who needs a basic overview of databases, unfortunately with some not-too-important details, for example, fifth normal form (5NF) and Voronoi diagrams. This unbalanced approach reduces the quality of the book.

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