DATABASE DEBUNKINGS

LOGICAL DESIGN: INTERPRETATION OF RDM SYMBOLIZED SETS

noreply@blogger.com (Fabian Pascal) — Tue, 10 Mar 2026 11:07:00 +0000

As we explain in Logical Database Design (forthcoming), LDD assigns the meaning of terms in conceptual models (CMs)—properties, entities, groups, multigroup—to non-logical symbols of a formal logic theory.

If the theory is RDM, the symbols stand for sets—domains/attributes, tuples, relations, database—adapted for database management. For each CM the theory acquires an interpretation, which produces a LM (application) of the theory for database representation and manipulation.

Here are the adapted sets symbolized in RDM which acquire the interpretation of the terms in CMs.

SEMANTICS, DATABASE RELATIONS, AND TABLES

noreply@blogger.com (Fabian Pascal) — Mon, 02 Mar 2026 04:09:00 +0000

This was said years ago:

”Table (n.) – a collection of information (data?) describing a population of entities which possess some common characteristics, called attributes. -itis – “suffix denoting diseases characterized by inflammation, itself often caused by an infection.” ---------- from the Wikipedia Wiktionary.”

Tables are the building block of relational databases. Tables must generally be “normalized,” at least to 1NF. That may be an appropriate way to think of databases when implemented in a modern day DBMS. However, it is not the way the world thinks logically. People have no problem with commonly occurring phenomena such as:

· A multi-valued attribute, e.g., an Employee possesses multiple Skills.

· Many-to-many (M:N) relationships, e.g., as between Employees and Projects

· A relationship with attributes

even though our systems may. None of these situations can be handled directly in a relational database."

This just now, on LinkedIn (check out my comments).

“Putting to one side the argument that your data almost certainly didn't start out broken out in to tables, and it almost certainly isn't consumed that way either, here's the thing; MongoDB, if you squint, is essentially a relational database with an unorthodox take on first normal form and some great high availability and scalability features.” -- Graeme Robinson

CONCEPTUAL MODELING FOR DATABASE DESIGN VERSION 2(2/26) PUBLISHED

noreply@blogger.com (Fabian Pascal) — Fri, 20 Feb 2026 03:40:00 +0000

This is a major re-write. Order from a PAPERS page.

Table of Contents

Introduction

1 Conceptual Modeling

1.1 Ontological Commitment

1.2 Relationships as Properties

2 Object-properties Modeling

2.1 Entity Properties

2.1.1 1^stOrder Properties

2.1.1.1 Names

2.1.2 2^nd Order Properties

2.2 3^rd Order Group Properties

2.2.1 Uniqueness 3OPs

2.2.2 Bounded Aggregate 3OPs

2.2.3 Meaning Criteria

2.3 4^th Order Multigroup Properties

2.3.1 Referential 4OPs

2.3.2 Aggregates 4OPs

3 Business Rules

3.1 Property Rules

3.1.1 1OP Rules

3.1.2. 1OPiC Rules

3.2 Object Type Rules

3.2.1 Entity Type Rules

3.2.1.1 1OPiCs-Entity Rules

3.2.1.2 2OP Rules

3.2.2 Group Type Rules

3.2.2.1 Uniqueness 3OP Rules

3.2.2.2 Aggregates 3OP Rules

3.2.3 Multigroup Type Rules

3.2.3.1 Referential 4OP Rules

3.2.3.2 Aggregates 4OP Rules

Conclusion

Appendix A: Quasi-Properties

FACTS, ENTITIES, AND BUSINESS RULES

noreply@blogger.com (Fabian Pascal) — Mon, 16 Feb 2026 04:54:00 +0000

“... In ORM there is no concept of an entity record (tuple), although relational tables can be automatically generated from an ORM model (furthermore, guaranteed to be fully normalized).” --Online comment

“Object Role Modeling (ORM) is a ...a fact-oriented modeling approach for specifying, transforming, and querying information at a conceptual level. Unlike [other modeling approaches] ... fact-oriented modeling is attribute-free, treating all elementary facts as relationships ... In practice, ORM data models often capture more business rules, and are easier to validate and evolve than data models in other approaches. --ORM.net

DATA MUDDLING

noreply@blogger.com (Fabian Pascal) — Mon, 02 Feb 2026 08:29:00 +0000

Chris Date once published an article at the old DBDebunk titled “Models, Models, Everywhere, Nor Any Time to Think”. If you want to get a hold of what he meant then, you oughta do a search on the title now and see what you get.

The continuous proliferation of models is an indication and measure of the disregard, if not outright hostility of the industry to sound theoretical foundations. It keeps reminding me of a decades-old piece I posted in response to David Hay's critique of Ron Ross's then proposal of a “fact model” (yet another one) as an alternative to data model. It is more relevant than ever, which is why I decided to bring it up to date. The problem is so entrenched and widespread, that even those who try to address it fail to realize that they are victims of it too.

Hay correctly observed:

“In our industry, there is a strong desire to put names on things. This is natural enough, given the amount of information that we have to classify and deal with in our work. To give something a name is to gain control over it, and this is not necessarily a bad thing. The problem is when the name takes the place of true understanding of the thing named. Discourse tends to be the bantering of names, without true understanding of the concepts involved.”

In this industry, many of the names are just re-labeling, whether it fits or not. Here are a couple of exquisite examples of both cases:

“I was amused to read in [Ralph Kimball's] article that my own suppliers and parts database design was "a perfect, beautiful star schema!" When I first learned the term "star schema", my reaction was that a properly designed star schema would be nothing neither more, nor less than a properly designed schema per se (in other words, one that did obey those scientific principles of relational design that do exist). So to see RK say that my schema was in fact a star schema reminded me (I’m afraid) of Peter Chen’s original E/R paper, in which—among other things—he reinvented the concept of domains, but called them value sets, and then went on to analyze the relational model in terms of his own ideas and said “Look, domains are just value sets!” --C. J. Date

Note: Kimball's "star schema" is, of course, not a relational schema, but quite an attempt to avoid it, due to failure to distinguish application views of the database from the database schema.

WHAT MEANING MEANS: BUSINESS RULES, PREDICATES, CONSTRAINTS, AND SEMANTIC CONSISTENCY

noreply@blogger.com (Fabian Pascal) — Sun, 25 Jan 2026 22:26:00 +0000

“If we step back and look at what RDBMS is, we’ll no doubt be able to conclude that, as its name suggests (i.e., Relational Database Management System), it is a system that specializes in managing the data in a relational fashion. Nothing more. Folks, it’s important to keep in mind that it manages the data, not the MEANING of the data! And if you really need a parallel, RDBMS is much more akin to a word processor than to an operating system. A word processor (such as the much maligned MS Word, or a much nicer WordPress, for example) specializes in managing words. It does not specialize in managing the meaning of the words ... So who is then responsible for managing the meaning of the words? It’s the author, who else? Why should we tolerate RDBMS opinions on our data? We’re the masters, RDBMS is the servant, it should shut up and serve. End of discussion.” --Alex Bunardzik, Should Database Manage The Meaning?

noreply@blogger.com (Fabian Pascal) — Tue, 23 Dec 2025 01:46:00 +0000

Revision 1 (6/25) of CONCEPTUAL MODELING FOR DATABASE DESIGN - A Sound Guide

noreply@blogger.com (Fabian Pascal) — Wed, 22 Jan 2025 05:14:00 +0000

Table of Contents

Introduction
1 Information Representation
2 Conceptual Modeling
2.1 Ontological Commitment
2. 2 Properties and Relationships
3. Entity Properties
3.1 First Order Properties
3.2 Assertion Predicates
3.3 Second Order Properties
4 Group Properties
4.1 Third Order Properties
4.1.1 Entity Uniqueness
4.1.2 1OP (in Context) Dependencies
4.1.3 Aggregates Relationships
4.1.4 Meaning Criteria and ESS Relationships
4.1.5 Designation “Property”
5 Multigroup Fourth Order Properties
5.1 Inter-group Entity Relationships
5.2 Inter-group Aggregates Relationships
6. Business Rules
6.1 Entity Type Rules
6.2 Group Type Rules
6.3 Multigroup Type Rules
Conclusion
Appendix: PoM/OCP and RDM

Revision 1 (7/25) of RELATIONAL DATABASE DOMAINS: A Definitive Guide

noreply@blogger.com (Fabian Pascal) — Wed, 22 Jan 2025 05:10:00 +0000

Table of Contents

Introduction
1 Formal Theory and Interpretation
2 Database Domains
2.1 Domains As Data Types
2.1.1 RDM and Programming Data Types
2.1.2 Abstract Data Types
2.2 Domain Definition
2.2.1 Type Specification
2.2.2 Domain Operators
3 Kinds of Domains
3.1 Base and Derived Domains
3.2 Primitive Domains
3.3 Atomic ("Simple") Domains
3.4 Complex (Derived) Domains
4 RDM Type System
5 DBMS Domain Support
Appendix 1: A Complex Domain Example
Appendix 2: A Note on SQL Built-in Data Types

New Paper: PRIMARY KEYS - A New Understanding

noreply@blogger.com (dbdebunker) — Tue, 14 Jan 2025 23:57:00 +0000

New Paper: THE FINAL NULL IN THE COFFIN - A Relational Solution to Missing Data

noreply@blogger.com (dbdebunker) — Tue, 14 Jan 2025 23:39:00 +0000

Ssason's Greetings!

noreply@blogger.com (Fabian Pascal) — Fri, 27 Dec 2024 19:47:00 +0000

New Paper: FIRST NORMAL FORM - A Definitive Guide

noreply@blogger.com (Fabian Pascal) — Mon, 22 Jul 2024 17:23:00 +0000

New Paper: UNDERSTANDING THE REAL RDM - E.F. Codd 1969-70 Papers Part 2

noreply@blogger.com (Fabian Pascal) — Sun, 14 Jul 2024 22:31:00 +0000

Table of Contents

Introduction
1. Logical Symmetric Access
2. Universal Data Sublanguage
2.1. FOPL vs. SOL
2.2. Relational Completeness
2.3. Computational Completeness and Hosting
3. Kinds of Relations
3.1. Expressible and Named Relations
3.2. Derived Relations
3.3. Data Storage
4. Derived Relations and Redundancy
4.1. Database Consistency
5. Database Catalog
Conclusion

New Paper: UNDERSTANDING THE REAL RDM - E.F.Codd 1969-70 Papers Part 1

noreply@blogger.com (Fabian Pascal) — Mon, 08 Jul 2024 15:33:00 +0000

Table of Contents

Series Preface
Introduction
1. Interpretation of Database Relations
1.1. Attributes as Constrained Domains
1.2. Time-Varying Relations
2. Representation of Database Relations
2.1. Physical Data Independence
2.1.1. Uniquely Named Attributes
2.1.2. Primary Keys
2.1.3. Relations and R-tables
3. Normalization
3.1. First Normal Form and “Simple” Domains
3.2. Normalization and Non-simple Domains
3.2.1. Foreign Keys
Conclusion

SQL AT 50, OR WHY THERE ARE NO RDBMS'S

noreply@blogger.com (Fabian Pascal) — Mon, 17 Jun 2024 17:13:00 +0000

In "Codd Almighty! Has it been half a century of SQL already?" the Register's Lindsay Clark interviews "Donald Chamberlin, Michael Stonebraker and more" about the legendary programming [sic] language. Chamberlin with Raymond Boyce were the authors of "the 1974 paper SEQUEL: A structured English query language as a way of addressing data in IBM's newly proposed System R, the first database to embody Edgar Codd's paper describing the relational model for database management.”

C. J. Date, who worked at IBM at the time, has often stated that the designers of SQL never understood RDM, and I expressed a similar stance in If You Liked SQL, You'll love XQuery. This has had an extremely detrimental effect on database technology--regress rather than progress--none of which transpires in the interview. So here is my reality check take on what you would not know from the interview.

SMS: DOMAINS & SQL

noreply@blogger.com (Fabian Pascal) — Sat, 01 Jun 2024 18:42:00 +0000

I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:

THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
PRIMARY KEYS - A NEW UNDERSTANDING

available for ordering from the PAPERS page, and two more:

RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
DATABASE RELATIONS: A DEFINITIVE GUIDE

are in progress and forthcoming, respectively.

In the process I am coming across common and entrenched industry "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispel some of those fallacies, treated in more depth in the papers, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here's one.

“A domain in most SQL usage is essentially an alias name for an existing type + restrictions on an existing type that can be used in a column. As for an attribute, it's essentially a COLUMN in SQL, a field in other types of databases, etc.”

Can you identify the fallacies before you proceed?

TLC: TABLES, DIMENSIONS & RDM

noreply@blogger.com (dbdebunker) — Sun, 12 May 2024 03:49:00 +0000

I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:

THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
PRIMARY KEYS - A NEW UNDERSTANDING

available for ordering from the PAPERS, and two more:

RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
DATABASE RELATIONS: A DEFINITIVE GUIDE

are in progress and forthcoming, respectively.

In the process, I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispel some of those fallacies, treated in more depth in the papers, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here's one.

“Data is stored in two-dimensional tables consisting of columns (fields) and rows (records). Multi-dimensional data is represented by a system of relationships among two-dimensional tables.”

My April FTD, TLC & SMS LinkedIn Posts

noreply@blogger.com (Fabian Pascal) — Thu, 02 May 2024 18:32:00 +0000

SMS: PRIMARY KEYS & INDEXES

noreply@blogger.com (Fabian Pascal) — Thu, 02 May 2024 18:25:00 +0000

I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:

THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
PRIMARY KEYS - A NEW UNDERSTANDING

available for ordering from the PAPERS page, and two more:

RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
DATABASE RELATIONS: A DEFINITIVE GUIDE

are in progress and forthcoming, respectively.

In the process I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispell some of those fallacies, treated in more depth in the papers, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here's one:

“There seams to be some confusion between what a Primary Key is, and what an Index is and how they are used. The Primary Key is a logical object. By that I mean that is simply defines a set of properties on one column or a set of columns to require that the columns which make up the primary key are unique and that none of them are null. Because they are unique and not null, these values (or value if your primary key is a single column) can then be used to identify a single row in the table every time. In most if not all database platforms the Primary Key will have an index created on it. An index on the other hand doesn’t define niqueness. An index is used to more quickly find rows in the table based on the values which are part of the index. When you create an index within the database, you are creating a physical object which is being saved to disk.”

Can you identify the fallacies before you proceed?

My March FTD, TLC & SMS LinkedIn Posts

noreply@blogger.com (dbdebunker) — Mon, 15 Apr 2024 23:40:00 +0000

TLC: RDM & COMPLEX DATA TYPES

noreply@blogger.com (Fabian Pascal) — Fri, 05 Apr 2024 22:43:00 +0000

I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:
THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
PRIMARY KEYS - A NEW UNDERSTANDING
available for ordering from the PAPERS page, and two more:
RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
DATABASE RELATIONS: A DEFINITIVE GUIDE
are in progress and forthcoming, respectively.

In the process I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispel some of those fallacies (treated in more depth in the papers) in short posts here, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here comes the first--a TLC I posted on LinkedIn.

“The company was using a [SQL] RDBMS . . . to handle data transactions for its trading applications. However, the applications required arbitrary data types, which is nearly impossible for relational systems, according to experts.”

which contains three fallacies--can you identify them before you proceed?

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"SQL RDBMS" is a contradiction in terms. Not only are SQL DBMSs not relational (and, thus, fail to provide RDM's advantages), but--even leaving SQL out--the interpretation (and, thus, understanding, such as it is) of RDM dominant in the industry is flawed. Do you know why, and what are the missed advantages?

"Arbitrary data types"--more precisely, domains of arbitrary complexity (not to be confused with SQL built-in types)--are not impossible in RDM properly understood, namely, as coupled with a strong type system: a notion of type hierarchy derived from a theory of types that governs manipulation of domain values, which is orthogonal to RDM, albeit necessary, for support of domains in general, and those so-called "complex" in particular (orthogonal in the sense that the relational data sublanguage is insulated from the implementation of the domains and their operators). Such a type system is incorporated in McGoveran's Semantic-Relational Data Model (SRDM)--the correct interpretation, extension and formalization of Codd's work.

As to "experts", I do not know many (to understate the case) in RDM and I assure you that the above statement was not made by any of them.

References

McGoveran, D., LOGIC FOR SERIOUS DATABASE FOLK (draft chapters), forthcoming.
Pascal, F., RELATIONAL DATABASE DOMAINS, forthcoming.

METALOGICAL PROPERTIES Part 2: Assertion Predicate

noreply@blogger.com (Fabian Pascal) — Mon, 05 Feb 2024 21:18:00 +0000

In Part 1 we introduced in the conceptual model (CM) the metalogical designation property. It represents—in the absence of known shared defining properties of an entity type, the designation by a group's definer that an entity identifier (aka assigned name) or property value is a member of the group. Such a group is not a group of entities, but a group of name and property values. In the logical model (LM), it is formalized as a designation predicate (DP) and defines a domain.

In Part 2, we introduce the metalogical assertion property. It represents the assertion by an authorized database user that a specific entity, represented by a tuple, either does or does not correspond to an actual entity in the real world.

METALOGICAL PROPERTIES PART 1: Designation Property

noreply@blogger.com (Fabian Pascal) — Wed, 10 Jan 2024 02:47:00 +0000

with David McGovern

One purpose of our contributions here is to suggest a vocabulary that avoids confusion not just within the formal logical level, but also between conceptual and logical terminologies, which is widespread in the industry and is exacerbated by limitations of natural language (NL). We use the following terminology in our approach to conceptual modeling:

Objects are:

- Primitive (basic entities);

- Compound:

- groups of related entities;

- multigroups (groups of related groups);

Properties are:

- Individual (of basic entities);

- Collective:

- Of groups: relationships among entities within a group;

- Of multigroups: relationships among groups within a multigroup.

Note: It is a McGoveran insight that relationships between objects at a lower aggregate level are properties of the object at the higher aggregate level which the former comprise (LOGIC FOR SERIOUS DATABASE FOLK, forthcoming; see draft chapters) http://www.alternativetech.com/ATpubs_dir.html For classification of properties as first, second, third and fourth order (1OP, 2OP, 3OP and 4OP) see RELATIONSHIPS AND THE RDM Parts 1-3. https://www.dbdebunk.com/2023/03/relationships-and-rdm-v2-part-1.html All such properties can be expressed logically in a FOPL-based relational data sublanguage as constraints, which is beyond the scope of this discussion.

HAPPY HOLIDAYS!

noreply@blogger.com (Fabian Pascal) — Wed, 22 Nov 2023 23:31:00 +0000

Due to:

1. Taking care of some health issues that have accumulated (not getting any younger);

2. Concentration on the Israel-Hamas War;

3. Effort to update old papers and write new ones;

4. Much needed rest and the holidays.

I am taking the remaining of the year off and will re-start my contributions in January.

Wishing you and yours season's greetings and happy holidays!