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SQL & NoSQL Databases de Andreas Meier

SQL & NoSQL Databases

Autor Andreas Meier, Michael Kaufmann
en Limba Engleză Paperback – 16 iul 2019

Suntem de părere că SQL & NoSQL Databases reprezintă o resursă tehnică esențială pentru studenții și profesioniștii din domeniul IT care posedă deja o bază solidă în informatică și doresc să stăpânească arhitecturile moderne de gestionare a datelor. Lucrarea necesită o înțelegere prealabilă a logicii programării și a structurilor de date, fiind concepută ca un ghid de implementare pentru sisteme complexe. Structura volumului este riguros organizată în șapte capitole cheie, pornind de la managementul datelor și modelare, până la arhitecturi de sistem și baze de date NoSQL. Dacă Principles of Database Management de Wilfried Lemahieu v-a oferit cadrul teoretic vast, această carte oferă instrumentele practice și specificațiile tehnice necesare pentru a naviga între sistemele omogene și cele eterogene. Autorii, Andreas Meier și Michael Kaufmann, pun un accent deosebit pe provocările consistenței datelor în sisteme distribuite masiv, oferind o comparație critică între modelele ACID și BASE. În contextul operei autorului, această lucrare consolidează direcția începută în Big Data Analytics, unde au fost introduse conceptele fundamentale de prelucrare a volumelor mari de date. Spre deosebire de abordările pur teoretice din Database Systems de Ramez Elmasri, volumul de față este extrem de aplicat, integrând peste 100 de ilustrații și exemple de Query by Example (QBE) și limbaje de interogare specifice bazelor de date graf sau document-store. Progresia logică a capitolelor permite cititorului să înțeleagă nu doar limitele SQL-ului tradițional, ci și potențialul bazelor de date fuzzy sau al structurilor multidimensionale.

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Specificații

ISBN-13: 9783658245481
ISBN-10: 3658245484
Pagini: 248
Ilustrații: XVI, 229 p. 113 illus., 111 illus. in color.
Dimensiuni: 168 x 240 x 14 mm
Greutate: 0.42 kg
Ediția:1st ed. 2019
Editura: SpringerGabler
Locul publicării:Wiesbaden, Germany

De ce să citești această carte

Recomandăm această carte inginerilor de date și arhitecților de sistem care au nevoie de o fundamentare tehnică precisă pentru alegerea tehnologiilor de stocare. Veți câștiga o perspectivă clară asupra diferențelor dintre Key-Value, Column-Family și Document Stores, învățând să optimizați consistența și performanța în aplicații de tip Big Data. Este un manual practic care transformă teoria bazelor de date în soluții arhitecturale viabile.

Despre autor

Andreas Meier este profesor emerit de informatică economică la Universitatea din Fribourg, specializat în managementul datelor și sisteme de informații. Michael Kaufmann, de asemenea expert în domeniu, contribuie cu o perspectivă actualizată asupra tehnologiilor emergente. Împreună, aceștia au publicat lucrări fundamentale în domeniul Big Data Analytics și Blockchain, fiind recunoscuți pentru capacitatea de a sintetiza inovațiile academice în ghiduri practice utilizate în universitățile de elită din spațiul DACH (Germania, Austria, Elveția).

Descriere scurtă

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.


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. 

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.  


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