Relational Database Systems

Theory and Practice
Erscheinungsjahr 2027
ISBN: 978-3-032-47678-4
Verlag: Springer

Buch, Englisch, Format (B × H): 155 mm x 235 mm

This book presents a structured introduction to relational databases, progressing from the relational model, relational algebra, and SQL to database design and normalization, physical storage and indexing, query processing and optimization, transactions, concurrency control, security, and distributed and parallel databases. It also examines analytical and procedural SQL and the management of JSON, XML, spatial, textual, vector, and graph data within modern relational systems.

Relational databases remain central to reliable data management, but contemporary applications increasingly combine structured data with heterogeneous formats and advanced search requirements. This book explains how established relational principles can support these workloads while preserving data integrity, performance, security, and maintainability.

Designed as both a learning resource and a practical reference, this book is intended for undergraduate and graduate students, instructors, software developers, database administrators, data engineers, analysts, and researchers. Its combination of theoretical foundations, design reasoning, and executable SQL helps readers progress from fundamental concepts to the implementation and evaluation of modern database solutions.

Zielgruppe

Graduate

Autoren/Hrsg.

Iacob, Felix

Dragan, Ioan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

.- Part I — Foundations of Data and Database Systems.
.- Introduction to Databases.
.- The Relational Model introduction.
.- Foundations of the Relational Model.
.- The Relational Model in Depth.
.- Entity–Relationship Modeling.
.- Part II — SQL and Data Manipulation.
.- SQL Data Definition and Manipulation.
.- Advanced SQL Queries.
.- SQL Programming and Security.
.- Part III — Database Design and Normalization.
.- Functional Dependencies and Normal Forms.
.- Advanced Design Topics.
.- Part IV — Implementation and Performance.
.- Physical Storage and Indexing.
.- Join Algorithms and Physical Query Execution.
.- Query Processing and Optimization.
.- Transaction Management and Concurrency Control.
.- Part V — Advanced and Emerging Topics.
.- Distributed and Parallel Databases.
.- Beyond Relational SQL.
.- Big Data and NoSQL Systems.
.- Graph Databases and Knowledge Graphs.
.- Real-Time and Streaming Databases.
.- Part VI — Autonomous, AI-Powered Self-Optimizing Engines.
.- Autonomous, AI-Powered Self-Optimizing Engines.
.- Security, Compliance, and Zero-Trust.
.- Machine Learning Inside Streaming Databases.
.- Cloud-Native and Serverless DBaaS as the New Default.
.- Part VII — Guide to Learning SQL Queries Using Scott’s Schema.

Über Autor(innen)

Felix Iacob is an Associate Professor of Computer Science and Physics at the West University of Timi?oara, Romania. He holds an M.Sc. in Computer Science and a Ph.D. in Quantum Physics, an interdisciplinary background that supports his teaching and research in database systems, scientific data processing, and computational modeling, including applications in astrophysics. He teaches database systems, advanced database systems, and computational methods across computer science, mathematics, and physics programs. His practical database experience includes working with international scientific data resources such as LXCat, KIDA, and database of the Astronomical Observatory of Belgrade. These resources collect, organize, and make complex physical and astronomical data accessible and understandable, while supporting data analysis, visualization, and graphical representation for the wider research community. He has also published peer-reviewed research and developed extensive teaching materials, and project specifications that connect relational database theory with practical implementation and data-intensive scientific research.

Ioan-Dumitru Dragan is a computer scientist whose research spans databases, cloud and distributed computing, data-intensive systems, formal software verification, automated reasoning, and computer vision. He holds a Ph.D. in Technical Sciences from TU Wien, where his doctoral research addressed first-order theorem proving for program analysis and theory reasoning. His work at Institute eAustria has contributed to European research projects concerned with reliable cloud infrastructures, heterogeneous computing, large-scale data processing, and the monitoring of data-intensive applications, including ASPIDE, DICE, and CloudLightning. His publications cover scalable monitoring platforms, cloud and high-performance computing, automated theorem proving, compiler verification, and distributed image-processing methods.