Follow @DBDebunk
Follow @ThePostWest
We've been there, done that.
In Coming Full Circle: Why SQL now powers the NoSQL Craze Ryan Betts, CTO at VoltDB, argues that NoSQL products should adopt SQL for queries. I don't know about you, but to me it looks like a contradiction. Let me make it clear that my intention here is neither to defend SQL, nor to criticize it--I sure have done enough of that during the years--but rather strictly debunk the notion that its use with NoSQL systems is a good idea.
Sunday, November 15, 2015
Sunday, November 8, 2015
Weekly Update
Follow @DBDebunk
Follow @ThePostWest
Housekeeping: Added
to LINKS page.
1. Quote of the Week
Housekeeping: Added
to LINKS page.
RAQUELto SOFTWARE section on Home page.
1. Quote of the Week
After attending NoSQL conference I am really hoping that companies think through this 'big data' implementation! No one there was interested in Data model ... and said so ... forget the data model ... even 'standards' were looked at 'its 'too early' for this new technology ... and no one could tell us anything about 'meta-data'...!!!!! --LinkedIn.com
Sunday, November 1, 2015
Re-write
Follow @DBDebunk
Follow @ThePostWest
See series starting at:
See series starting at:
The Principle of Orthogonal Database Design Part I
Sunday, October 25, 2015
Weekly Update
Follow @DBDebunk
Follow @ThePostWest
1. Quote of the Week
1. Quote of the Week
The ER notation consists a set of constructs, such as, a rectangle to represent an entity types, an ellipse to represent an attribute a diamond to represent a relationship type, and so on. The RDS is a set of linear relation schemas. A relation schema has a name and is a sequence of attributes of text separated by comas and arranged horizontal. I have also developed an ER-to relational transformation algorithm to transform an ER schema to its corresponding RDS. I wish to implement this project as a CASE tool. --LinkedIn.comThe problem is not the student, but the quality of education he gets at his university.
Wednesday, October 21, 2015
Mathematics & Meaning
Follow @DBDebunk
Follow @ThePostWest
My October column @AllAnalytics.
We have seen that the usefulness of the relational data model (RDM) is in its dual theoretical foundation -- first order predicate logic (FOPL) and set theory -- the mathematics guarantees provable logical correctness of query results regardless what meaning is assigned to the database R-tables. But a logically correct result is not necessarily a meaningful result. As a reader commented "If a is Salary and b is Start date, the [Cartesian] product a*b still doesn't have a sensible meaning." It is critical for the analyst to understand the distinction.
Read it all. (Please comment there, not here)
My October column @AllAnalytics.
We have seen that the usefulness of the relational data model (RDM) is in its dual theoretical foundation -- first order predicate logic (FOPL) and set theory -- the mathematics guarantees provable logical correctness of query results regardless what meaning is assigned to the database R-tables. But a logically correct result is not necessarily a meaningful result. As a reader commented "If a is Salary and b is Start date, the [Cartesian] product a*b still doesn't have a sensible meaning." It is critical for the analyst to understand the distinction.
Read it all. (Please comment there, not here)
Sunday, October 18, 2015
Re-write
Follow @DBDebunk
Follow @ThePostWest
See series starting at
See series starting at
The First Normal Form in Theory and Practice, Part I
Sunday, October 11, 2015
Weekly Update (UPDATED)
Follow @DBDebunk
Follow @ThePostWest
Housekeeping: Added following to LINKS page:
1. Quote of the Week
Housekeeping: Added following to LINKS page:
- Why is it so hard to get SQL performance right the first time
- Why Are There No Relational DBMS's
- SchemeUnit and SchemeQL: Two Little Languages
1. Quote of the Week
"The real definition of Big Data?? Simple: Whatever does not fit in Excel!"
Me: What is--precisely, pls!--the threshold from small to big data? And how do the structural, manipulative and integrity aspects change over the threshold?
HM: Big data := the smallest set of data for which the sensitivity of your transfer function is minimal, and such that the cardinality of this set is too large to implement said transfer function on a single physical machine.Transfer function := though not strictly a function, as in the Lambda calculus, it is more of an operator which ingests data of any size and produces a monetizeable product or service. Sensitivity := the degree to which a perturbation on the input into a transfer function affects the result produced by said function.
Me: Ugh! I'm sure that's exactly what all the overnight data scientists, including those who invented Big Data, had in mind.--LinkedIn.com
Subscribe to:
Posts (Atom)