Advanced Data Management

This graduate text book provides a formal analysis of alternative, non-relational data models and storage mechanisms and gives a decent overview of non-SQL query languages. It describes a perspective beyond SQL and relational database management systems and thus covers the theoretical background of modern data management. It also helps to take informed decisions about what database systems to use.

Lena Wiese , University of Göttingen, Germany.

Advanced data management has always been at the core of efficient database and information systems. Recent trends like big data and cloud computing have aggravated the need for sophisticated and flexible data storage and processing solutions.
This book provides a comprehensive coverage of the principles of data management developed in the last decades with a focus on data structures and query languages. It treats a wealth of different data models and surveys the foundations of structuring, processing, storing and querying data according these models.

Starting off with the topic of database design, it further discusses weaknesses of the relational data model, and then proceeds to convey the basics of graph data, tree-structured XML data, key-value pairs and nested, semi-structured JSON data, columnar and record-oriented data as well as object-oriented data. The final chapters round the book off with an analysis of fragmentation, replication and consistency strategies for data management in distributed databases as well as recommendations for handling polyglot persistence in multi-model databases and multi-database architectures.

While primarily geared towards students of Master-level courses in Computer Science and related areas, this book may also be of benefit to practitioners looking for a reference book on data modeling and query processing. It provides both theoretical depth and a concise treatment of open source technologies currently on the market.

Autorentext

Lena Wiese, University of Göttingen, Germany.