The fundamental assumption of the relational model is that all data are represented as mathematical relations, i.e., a subset of the Cartesian product of n sets. In the mathematical model, reasoning about such data is done in two-valued predicate logic (that is, without
NULLs), meaning there are two possible evaluations for each proposition: either true or false. Data are operated upon by means of a relational calculus and algebra.
The relational data model permits the designer to create a consistent logical model of information, to be refined through database normalization. The access plans and other implementation and operation details are handled by the DBMS engine, and should not be reflected in the logical model. This contrasts with common practice for SQL
DBMSs in which performance tuning often requires changes to the logical model.
The basic relational building block is the domain, or data type. A tuple is an ordered multiset of attributes, which are ordered pairs of domain and value. A relvar (relation variable) is a set of ordered pairs of domain and name, which serves as the header for a relation. A relation is a set of tuples. Although these relational concepts are mathematically defined, they map loosely to traditional database concepts. A table is an accepted visual representation of a relation; a tuple is similar to the concept of row.
The basic principle of the relational model is the Information Principle: all information is represented by data values in relations. Thus, the relvars are not related to each other at design time: rather, designers use the same domain in several relvars, and if one attribute is dependent on another, this dependency is enforced through referential integrity.
from wikipedia.org