Database Design Overview

Principles

Definition

Database design is the academic discipline and methodological process for structuring data and defining relationships within a database system. It involves the systematic application of principles and techniques for organizing data requirements into a formal model. This field investigates the optimal representation and organization of data to ensure integrity, consistency, and efficient access, characterized by stages such as conceptual, logical, and physical modeling and the application of principles like normalization. Its significance lies in providing the foundational structure necessary for developing reliable, scalable, and performant information systems.

Ontological type

Core Methods

Normalization Principles

Data Modeling Paradigms

Key developments

Key Figures

Relational Foundations and Extensibility era

E. F. Codd [1]'s central role in the Relational Foundations and Extensibility era is reflected by his association with Menlo School [3] during this period. Codd [1]'s key contributions in this era include extending the database relational model to capture more meaning [6] and the broader relational model for large shared data banks [5], which established rigorous design principles and data-independence foundations that guided later extensible systems. John Miles Smith [2] is another key contributor in this era, with ties to University of Utah [4]. Smith [2]'s 1977 paper Database abstractions [7] articulated higher-level data models and interface abstractions that informed subsequent extensibility and object-relational features in relational DBMS.

Heterogeneous Data Integration era

Gio Wiederhold [1], a leading figure in this era, is associated with Stanford University [3] and Aalborg University [4]. His papers, Mediators in the architecture of future information systems [6] and Flexible relation: an approach for integrating data from multiple, possibly inconsistent databases [7], articulated mediator architectures and schema reconciliation that enabled coherent access across heterogeneous databases, a central goal of the era. Matteo Golfarelli [2], notable in this era, is affiliated with University of Bologna [5]. Golfarelli [2] contributed Conceptual design of data warehouses from E/R schemes [8], a modeling-driven approach that bridged E/R modeling with data warehouse design to support analytical processing across heterogeneous sources in the era.

Schema Evolution and Interoperability era

Sebastian Link[1] is a scholar active across Universität Hamburg[3] and University of Auckland[4] during the Schema Evolution and Interoperability era. His key contributions in this era include exploring the implication problem of data dependencies over SQL table definitions [7], articulating possible and certain keys for SQL [9], and detailing SQL schema design: foundations, normal forms, and normalization [8], which together advanced formal constraint reasoning and practical guidance for interoperable schema evolution. Anastasia Ailamaki[2] is affiliated with École Polytechnique Fédérale de Lausanne[5] and University of Toronto[6] during this era. Her sole paper H2O (2014) [10] contributed to understanding data-system design with implications for interoperable storage in multi-model ecosystems.