Type inheritance is that phenomenon according to which we can say, for example, that every square is also a rectangle, and so properties that apply to rectangles in general apply to squares in particular. In other words, squares are a subtype of rectangles, and rectangles are a supertype of squares. Recognizing and acting upon such subtype / supertype relationships provides numerous benefits: Certainly it can help in data modeling, and it can also provide for code reuse in applications. For these reasons, many languages, including the standard database language SQL, have long supported such relationships. However, there doesn’t seem to be any consensus in the community at large on a formal, rigorous, and abstract model of inheritance. This book proposes such a model, one that enjoys several advantages over other approaches, not the least of which it is that it’s fully compatible with the well known relational model of data. Topics the model covers include: Both single and multiple inheritance Scalar, tuple, and relation inheritance Type lattices and union and intersection types Polymorphism and substitutability Compile time and run time binding All of these topics are described in detail in the book, with numerous illustrative examples, exercises, and answers. The book also discusses several alternative approaches. In particular, it includes a detailed discussion and analysis of inheritance as supported in the SQL standard.

E. F. Codd’s relational model of data has been described as one of the three greatest inventions of all time (the other two being agriculture and the scientific method), and his receipt of the 1981 ACM Turing Award, the top award in computer science, for inventing it was thoroughly deserved. The papers in which Codd first described his model were staggering in their originality; they had, and continue to have, a huge impact on just about every aspect of the way we do business in the world today. And yet few people, even in the professional database community, are truly familiar with those papers. This book—a thorough overhaul and rewrite of an earlier book by the same name—is an attempt to remedy this sorry state of affairs. In it, well known author C. J. Date provides a detailed examination of all of Codd’s major database publications, explaining the nature of his contribution in depth, and in particular highlighting not only the many things he got right but also some of the things he got wrong. Database theory and practice have evolved considerably since Codd first defined his relational model, back in 1969. This book draws on decades of experience to present the most up to date treatment of the material possible. Anyone with a professional interest in databases can benefit from the insights it contains. The book is product independent.

E. F. Codd's relational model of data has been described as one of the three greatest inventions of all time (the other two being agriculture and the scientific method), and his receipt of the 1981 ACM Turing Award-the top award in computer science-for inventing it was thoroughly deserved. The papers in which Codd first described his model were staggering in their originality; they had, and continue to have, a huge impact on just about every aspect of the way we do business in the world today. And yet few people, even in the professional database community, are truly familiar with those papers. This book is an attempt to remedy this sorry state of affairs. In it, well known author C. J. Date provides a detailed examination of all of Codd's major technical publications, explaining the nature of his contribution in depth, and in particular highlighting not only the many things he got right but also some of the things he got wrong.

Understanding SQL's underlying theory is the best way to guarantee that your SQL code is correct and your database schema is robust and maintainable. On the other hand, if you're not well versed in the theory, you can fall into several traps. In SQL and Relational Theory, author C.J. Date demonstrates how you can apply relational theory directly to your use of SQL. With numerous examples and clear explanations of the reasoning behind them, you'll learn how to deal with common SQL dilemmas, such as: Should database access granted be through views instead of base tables? Nulls in your database are causing you to get wrong answers. Why? What can you do about it? Could you write an SQL query to find employees who have never been in the same department for more than six months at a time? SQL supports "quantified comparisons," but they're better avoided. Why? How do you avoid them? Constraints are crucially important, but most SQL products don't support them properly. What can you do to resolve this situation? Database theory and practice have evolved since Edgar Codd originally defined the relational model back in 1969. Independent of any SQL products, SQL and Relational Theory draws on decades of research to present the most up-to-date treatment of the material available anywhere. Anyone with a modest to advanced background in SQL will benefit from the many insights in this book.

This book is a revised, upgraded, and hugely improved version of an earlier one called Logic and Databases. Although it’s effectively a brand new book, therefore, the following remarks from that earlier book are still relevant here. First, logic and databases are inextricably intertwined. The relational model itself is essentially just elementary logic, tailored to database needs. Now, if you’re a database professional, this won’t be news to you—but you still might not realize just how much everything we do in the database world is (or should be!) affected by logic. Logic is fundamental, and everywhere. As a database professional, therefore, you owe it to yourself to understand the basics of formal logic, and you ought to be able to explain (and perhaps defend) the connections between formal logic and database technology. And that’s what this book is about. What it does is show, through a series of partly independent, partly interrelated essays, just how various crucial aspects of database technology—some of them very familiar, others maybe less so—are solidly grounded in formal logic. Overall, the goal is to help you realize the importance of logic in everything you do, and also, I hope, to help you see that logic can be fun.

Fifty years of relational. It’s hard to believe the relational model has been around now for over half a century! But it has—it was born on August 19th, 1969, when Codd’s first database paper was published. And Chris Date has been involved with it for almost the whole of that time, working closely with Codd for many years and publishing the very first, and definitive, book on the subject in 1975. In this book’s title essay, Chris offers his own unique perspective (two chapters) on those fifty years. No database professional can afford to miss this one of a kind history. But there’s more to this book than just a little personal history. Another unique feature is an extensive and in depth discussion (nine chapters) of a variety of frequently asked questions on relational matters, covering such topics as mathematics and the relational model; relational algebra; predicates; relation valued attributes; keys and normalization; missing information; and the SQL language. Another part of the book offers detailed responses to critics (four chapters). Finally, the book also contains the text of several recent interviews with Chris Date, covering such matters as RM/V2, XML, NoSQL, The Third Manifesto, and how SQL came to dominate the database landscape.

Time and Relational Theory provides an in-depth description of temporal database systems, which provide special facilities for storing, querying, and updating historical and future data. Traditionally, database management systems provide little or no special support for temporal data at all. This situation is changing because: - Cheap storage enables retention of large volumes of historical data in data warehouses - Users are now faced with temporal data problems, and need solutions - Temporal features have recently been incorporated into the SQL standard, and vendors have begun to add temporal support to their DBMS products Based on the groundbreaking text Temporal Data & the Relational Model (Morgan Kaufmann, 2002) and new research led by the authors, Time and Relational Theory is the only book to offer a complete overview of the functionality of a temporal DBMS. Expert authors Nikos Lorentzos, Hugh Darwen, and Chris Date describe an approach to temporal database management that is firmly rooted in classical relational theory and will stand the test of time. This book covers the SQL:2011 temporal extensions in depth and identifies and discusses the temporal functionality still missing from SQL. - Understand how the relational model provides an ideal basis for taming the complexities of temporal databases - Learn how to analyze and evaluate commercial temporal products with this timely and important information - Be able to use sound principles in designing and using temporal databases - Understand the temporal support recently added to SQL with coverage of the new SQL features in this unique, accurate, and authoritative reference - Appreciate the benefits of a truly relational approach to the problem with this clear, user friendly presentation

What makes this book different from others on database design? Many resources on design practice do little to explain the underlying theory, and books on design theory are aimed primarily at theoreticians. In this book, renowned expert Chris Date bridges the gap by introducing design theory in ways practitioners can understand—drawing on lessons learned over four decades of experience to demonstrate why proper database design is so critical in the first place. Every chapter includes a set of exercises that show how to apply the theoretical ideas in practice, provide additional information, or ask you to prove some simple theoretical result. If you’re a database professional familiar with the relational model, and have more than a passing interest in database design, this book is for you. Questions this book answers include: Why is Heath’s Theorem so important? What is The Principle of Orthogonal Design? What makes some JDs reducible and others irreducible? Why does dependency preservation matter? Should data redundancy always be avoided? Can it be? Databases often stay in production for decades, and careful design is critical for avoiding subtle errors and processing problems over time. If they’re badly designed, the negative impacts can be incredibly widespread. This gentle introduction shows you how to use important theoretical results to create good database designs.

This book constitutes the proceedings of the 26th European Conference on Advances in Databases and Information Systems, ADBIS 2022, held in Turin, Italy, in September 2022. The 29 short papers presented were carefully reviewed and selected from 90 submissions. The selected short papers are organized in the following sections: data understanding, modeling and visualization; fairness in data processing; data management pipeline, information and process retrieval; data access optimization; data pre-processing and cleaning; data science and machine learning. Further, papers from the following workshops and satellite events are provided in the volume: DOING: 3rd Workshop on Intelligent Data – From Data to Knowledge; K-GALS: 1st Workshop on Knowledge Graphs Analysis on a Large Scale; MADEISD: 4th Workshop on Modern Approaches in Data Engineering and Information System Design; MegaData: 2nd Workshop on Advanced Data Systems Management, Engineering, and Analytics; SWODCH: 2nd Workshop on Semantic Web and Ontology Design for Cultural Heritage; Doctoral Consortium.

Some things seem so obvious that they don’t need to be spelled out in detail. Or do they? In computing, at least (and probably in any discipline where accuracy and precision are important), it can be quite dangerous just to assume that some given concept is “obvious,” and indeed universally understood. Serious mistakes can happen that way! The first part of this book discusses features of the database field—equality, assignment, naming—where just such an assumption seems to have been made, and it describes some of the unfortunate mistakes that have occurred as a consequence. It also explains how and why the features in question aren’t quite as obvious as they might seem, and it offers some advice on how to work around the problems caused by assumptions to the contrary. Other parts of the book also deal with database issues where devoting some preliminary effort to spelling out exactly what the issues in question entailed could have led to much better interfaces and much more carefully designed languages. The issues discussed include redundancy and indeterminacy; persistence, encapsulation, and decapsulation; the ACID properties of transactions; and types vs. units of measure. Finally, the book also contains a detailed deconstruction of, and response to, various recent pronouncements from the database literature, all of them having to do with relational technology. Once again, the opinions expressed in those pronouncements might seem “obvious” to some people (to the writers at least, presumably), but the fact remains that they’re misleading at best, and in most cases just flat out wrong.