Basics of Relational Data Model

Edgar Codd proposed Relational Data Model in 1970.


It is a representational or implementation data model.

Using this representational (or implementation) model we represent a database as collection of relations.

The notion of relation here is different from the notion of relationship used in ER modeling.

Relation is the main construct for representing data in relational model.
Every relation consists of a relation schema and Relation instance.



Relation Schema is denoted by  R (A1, A2, A3,……., An),

Customer (Customer ID, Tax ID, Name, Address, City, State, Zip, Phone, Email,Sex)

R--> Relation Name
Ai--> Attributes Name

The number of columns in a relation is known as its degree or arity’.

Relation instance or Relation State (r) of R (thought of as a table)
Each row in the table represents a collection of related data.
Each row contains facts about some entity of same entity-set.

        R = (A1, A2, A3,……., An)
        r(R) is a set of n tuples in R
        r = {t1, t2, t3,…….,tn}

r is an instance of R each t is a tuple and is a ordered list of values.
   
t = (v1  , v2 ,…, vn ) where vi  is an element of domain of Ai   


Characteristics of a  Relation:

Ordering of tuples  is not significant.

Ordering of values in a tuple is  important.

Values in a tuple under each column must be atomic (simple & single).