This book introduces readers to the field of relational (SQL) and non-relational (NoSQL) databases. The main topics covered are data management, data modeling, query and manipulation languages, consistency, privacy and security, system architectures and multi-user operation. The book also provides an overview of post-relational and non-relational database systems. In addition to classic concepts, important aspects of NoSQL databases are discussed, such as map / reduce, distribution options (fragments, replication), and the CAP theorem (Consistency, Availability, and Partition tolerance). The book will benefit students looking for an introduction to the area of SQL and NoSQL databases, as well as practitioners, helping them better understand the strengths and weaknesses of relational and non-relational approaches and developments in connection with big data applications.

Content

The authors

Andreas Meier is a former member of the Faculty of Economics and Social Science and was a Professor of Information Technology at the University of Fribourg. He specializes in electronic business, electronic government, and information management. He is member of the GI (Gesellschaft fr Informatik), IEEE Computer Society, and ACM.

Michael Kaufmann is a Professor of Data Science and Big Data at the School of Information Technology, Lucerne University of Applied Sciences and Arts. He is also the coordinator of the university's Data Intelligence research team, which develops and studies methods and technologies for intelligent data management.

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
  

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
  

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.