SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management
Autor Andreas Meier, Michael Kaufmannen Limba Engleză Paperback – 16 iul 2019
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
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
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
This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.
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Specificații
ISBN-13: 9783658245481
ISBN-10: 3658245484
Pagini: 229
Ilustrații: XVI, 229 p. 113 illus., 111 illus. in color.
Dimensiuni: 168 x 240 x 13 mm
Greutate: 0.4 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Vieweg
Locul publicării:Wiesbaden, Germany
ISBN-10: 3658245484
Pagini: 229
Ilustrații: XVI, 229 p. 113 illus., 111 illus. in color.
Dimensiuni: 168 x 240 x 13 mm
Greutate: 0.4 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Vieweg
Locul publicării:Wiesbaden, Germany
Cuprins
Data Management.- Data Modeling.- Database Languages.- Ensuring Data Consistency.- System Architecture.- Post-Relational Databases.- NoSQL Databases.
Notă biografică
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 für Informatik), IEEE Computer Society, and ACM. After studying music in Vienna, he graduated with a degree in mathematics at the Federal Institute of Technology (ETH) in Zurich, studied his doctorate, and qualified as a university lecture at the Institute of Computer Science. He was a systems engineer at the IBM research lab in San José, California, director of an international bank, and a member of the executive board of an insurance company.
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 DataIntelligence research team, which develops and studies methods and technologies for intelligent data management. Michael Kaufmann studied computer science, law and psychology at the University of Fribourg. With extra-occupational doctoral studies, he received his Ph.D. in computer science on the topic of inductive fuzzy classification in marketing analytics. He worked at PostFinance as a data warehouse poweruser in corporate development; Later on at Mobiliar Insurance as a data architect in the enterprise architecture unit; and as a business analyst at FIVE Informatik AG, where he initiated and led a research project and started teaching as a part time lecturer at Kalaidos University of Applied Science. Since 2014 he has been working at the Lucerne University of Applied Sciences and Arts in teaching and research as a lecturer for databases, where he founded and successfully funded the research team data intelligence.
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 DataIntelligence research team, which develops and studies methods and technologies for intelligent data management. Michael Kaufmann studied computer science, law and psychology at the University of Fribourg. With extra-occupational doctoral studies, he received his Ph.D. in computer science on the topic of inductive fuzzy classification in marketing analytics. He worked at PostFinance as a data warehouse poweruser in corporate development; Later on at Mobiliar Insurance as a data architect in the enterprise architecture unit; and as a business analyst at FIVE Informatik AG, where he initiated and led a research project and started teaching as a part time lecturer at Kalaidos University of Applied Science. Since 2014 he has been working at the Lucerne University of Applied Sciences and Arts in teaching and research as a lecturer for databases, where he founded and successfully funded the research team data intelligence.
Textul de pe ultima copertă
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
Data Management - Data Modeling - Database Languages - Ensuring Data Consistency - System Architecture - Post-Relational Databases - NoSQL Databases 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 für 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.
Content
Data Management - Data Modeling - Database Languages - Ensuring Data Consistency - System Architecture - Post-Relational Databases - NoSQL Databases 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 für 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.
Caracteristici
Explores relational (SQL) and non-relational (NoSQL) databases Covers database management, modeling, languages, consistency, architecture and more Extensively illustrated with more than 100 tables, examples and illustrations