Sunday, June 28, 2020

TYFK: Misconceptions About the Relational Model


“The most popular data model in DBMS is the Relational Model. It is more scientific a model than others. This model is based on first-order predicate logic and defines a table as an n-ary relation. The main highlights of this model are:
  • Data is stored in tables called relations.
  • Relations can be normalized, [in which case] values saved are atomic values.
  • Each row in a relation contains a unique value.
  • Each column in a relation contains values from a same domain.”

Each "Test Your Foundation Knowledge" post presents one or more misconceptions about data fundamentals. To test your knowledge, first try to detect them, then proceed to read our debunking, which is based on the current understanding of the RDM, distinct from whatever has passed for it in the industry to date. If there isn't a match, you can acquire the knowledge by checking out our POSTS, BOOKS, PAPERS, LINKS (or, better, organize one of our on-site SEMINARS, which can be customized to specific needs).

Friday, June 12, 2020

Semantics and the Relational Model

“The RDM is semantically weak ... struggles with consistent granularity and has limitations at the property level... it has no concept of data flow ... it is an incomplete theory. Great for its time but needs something better now ... it uses ill defined and linguistically suspect labels ... it has no rules for semantic accuracy ... this just makes the RDM 1% of the truth ... the RDM should have solved this all by now ... but it has clearly not. You fail to see the reality of the failure of RDM in the real world ... this is your choice. I understand why you cling to it ... it is a most excellent theory that I respect greatly ... [but o]pen minds make progress...” 
Thus in a LinkedIn exchange. Criticism of the RDM almost always reflects poor foundation knowledge and lack of familiarity with the history of the field, and as we shall see, this one is not different. It is often triggered by what I call the "fad-to-fad cookbook approach", one of the latest fads being the industry's revelational "discovery" of semantics.

Thursday, May 28, 2020

No Such Thing As "Current Relational Data Models"

“... the concept of a state group is indeed a missing modeling concept in relational/current data models...”

Thus in a LinkedIn exchange. I don't know what a "state group" is, but I spent almost six decades debunking the misuses of data model in general and the abuses of the RDM in particular and I smell them from miles away. While the time when lack of foundation knowledge shocked me is long gone, practitioners' total unawareness of and indifference to it, and poor reasoning in a field founded on logic never ceases to amaze me.

What exactly are "relational/current data models"?

Sunday, May 10, 2020

TYFK: What Is A Database Relationship?

Note: This is a re-write of an earlier post. About TYFK posts (Test Your Foundation Knowledge) see the post insert below.

“Here two or more table[s] are related with each other. This is Database relationship. Database relationship is used a lot ... [in] relational database management systems ... shortly called RDBMS. Here is Join_data [sic] table and Interview_data table. For creating a relational database management system both of the table[s] must have a common field. Here Employee_ID is a common field ... Database relationship types: One-To-One relation, One-To-many relation, Many-to-many relation. Minimum one common field is essential in all the tables. The data type of common field and field size will be same in all the tables.”
First try to detect the misconceptions, then check against our debunking. If there isn't a match, you can acquire the necessary foundation knowledge in our POSTS, BOOKS, PAPERS, LINKS or, better, organize one of our on-site SEMINARS, which can be customized to specific needs.


Monday, April 27, 2020

TYFK: "Multi-model DBMSs" is an Empty Set


Note: About TYFK posts (Test Your Foundation Knowledge) see the post insert below.
“Traditional databases ... don't have a multi-model capability. Point is that richer data models are underused, relational data models are overused, and graph data models have so many advantages that shouldn't be ignored. Relational models, on the other hand, have wildly complex structures often with hundreds to thousands of tables. Each table then contains tens to hundreds of columns, arbitrarily constructed in each and every relational system. And just in case the situation wasn't complex enough, many of those columns are exist exclusively to manage uniqueness and provide connections to other tables. This Structure-FIrst approach produced the cascade of complexity from which we have struggled to recover ever since.”

First try to detect the misconceptions, then check against our debunking. If there isn't a match, you can acquire the necessary foundation knowledge in our POSTS, BOOKS, PAPERS, LINKS or, better, organize one of our on-site SEMINARS, which can be customized to specific needs.

Monday, March 23, 2020

TYFK: How (Not) to Compare NoSQL Systems and RDBMSs?


Note: About TYFK posts (Test Your Foundation Knowledge) see the post insert below.
“But if you still want to compare NOSQL databases with RDBMS, they primarily vary in
1. "normalization" where RDBMS contains normalized (upto certain degree) data and NOSQL based database contains non-normalized data;
2. RDBMS based databases are (I MUST say, generally and it isn't a criteria) fully ACID compliant while NOSQL databases are partially ACID compliant.
3. RDBMS are much slower and difficult to scale while NOSQL databases are much faster and easily scalable.
4. RDBMS normalization was very useful 50 years ago when cost of disk and memory was high, and computation power was limited. With the revolution in computing power, cheapest disk and memory availability has made RDBMS normalization a matter of joke - many people do not really understand why they need to normalize data in today's time.”
First try to detect the misconceptions, then check against our debunking. If there isn't a match, you can acquire the necessary foundation knowledge in our POSTS, BOOKS, PAPERS, LINKS or, better, organize one of our on-site SEMINARS, which can be customized to specific needs.

Note: In what follows RDBMS refers to a truly relational DBMS (of which currently aren't any), not to be confused with a SQL DBMS.

Thursday, March 12, 2020

Muddling Modeling Part 2: An Example


In an old article I used a Hay-Ross exchange to illustrate how disregard for fundamentals and the associated name proliferation -- which underlies the industry's fad-to-fad tradition -- cause confusion that inhibits understanding of conceptual modeling for database design. A recent LinkedIn exchange -- hardly unique -- showed the article to be as relevant today as it was two decades ago, prompting me to bring it up to date.

In Part 1 we reiterated pertinent fundamentals. Here is the re-written article
-- try to apply the fundamentals from Part 1 before you proceed with our debunking.

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