RDBMS

► Data redundancy & inconsistency.

► Difficult in accessing data.

► Data isolation.

► Data integrity.

► Concurrent access is not possible.

► Security Problems.

The are three levels of abstraction:

► Physical level: The lowest level of abstraction describes how data are stored.

► Logical level: The next higher level of abstraction, describes what data are stored in database and what relationship among those data.

► View level: The highest level of abstraction describes only part of entire database.

Redundancy is controlled. Unauthorised access is restricted. Providing multiple user interfaces. Enforcing integrity constraints. Providing backup and recovery.

There are two Integrity rules.

► Entity Integrity: States that ?Primary key cannot have NULL value?

► Referential Integrity: States that ?Foreign Key can be either a NULL value or should be Primary Key value of other relation.

The database and DBMS software together is called as Database system.

It is a collection of programs that enables user to create and maintain a database. In other words it is general-purpose software that provides the users with the processes of defining, constructing and manipulating the database for various applications.

A database is a logically coherent collection of data with some inherent meaning, representing some aspect of real world and which is designed, built and populated with data for a specific purpose.

It is a collection of all entities of particular entity type in the database.

This model is based on collection of objects. An object contains values stored in instance variables with in the object. An object also contains bodies of code that operate on the object. These bodies of code are called methods. Objects that contain same types of values and the same methods are grouped together into classes.

E-R model stands for Entity-Relationship model. This data model is based on real world that consists of basic objects called entities and of relationship among these objects. Entities are described in a database by a set of attributes.

It is a collection (set) of entities that have same attributes.

Given a relation R and a set of FDs F, dependency preservation states that the closure of the union of the projection of F on each decomposed relation Ri is equal to the closure of F. i.e.,

((?R1(F)) U … U (?Rn(F)))+ = F+

if decomposition is not dependency preserving, then some dependency is lost in the decomposition.

Equi Join: This is the most common type of join which involves only equality comparisions. The disadvantage in this type of join is that there

A relation schema R is said to be in 4NF if for every Multivalued dependency X --> Y that holds over R, one of following is true

► X is subset or equal to (or) XY = R.

► X is a super key.

A relation schema R is in BCNF if it is in 3NF and satisfies an additional constraint that for every FD X --> A, X must be a candidate key.

Proactive Update:

The updates that are applied to database before it becomes effective in real world .

Retroactive Update:

The updates that are applied to database after it becomes effective in real world .

Simulatneous Update:

The updates that are applied to database at the same time when it becomes effective in real world .

A relation schema R is in 3NF if it is in 2NF and for every FD X --> A either of the following is true

► X is a Super-key of R.

► A is a prime attribute of R.

In other words, if every non prime attribute is non-transitively dependent on primary key.

t is based on concept of full functional dependency. A functional dependency X --> Y is full functional dependency if removal of any attribute A from X means that the dependency does not hold any more.

A relation schema R is in 2NF if it is in 1NF and every non-prime attribute A in R is fully functionally dependent on primary key.