A labeled rectangle represents the corresponding
entity or record type. An arrow represents the set type, which denotes the
relationship between the owner record type and member record. The
arrow direction is from the owner record type to the member record
type.
A labeled rectangle represents the corresponding
entity or record type. An arrow represents the set type, which denotes the
relationship between the owner record type and member record. The
arrow direction is from the owner record type to the member record
type.
Each many to many relationship is handled by
introducing a new record type to represent the relationship wherein the
attributes, if any, of the relationship are stored. We when create two
symmetrical 1:M sets with the member in each of the sets being the
newly introduced record type. In this model, the relationships as well as
the navigation through the database are predefined at database creation
time.
In relational model
the data and the relations among them
are represented by a collection of tables. A tables is a collection of
records and each record in a table contains the same fields. The
attractiveness of the relational approach arouses from the simplicity in
the data organization and the availability of ably simple to very powerful
query languages. The relational model is based on a technique called
“Normalization” proposed by E.F. Codd. This model reduces the
complexity of the Network and Hierarchical Models. This model uses
the certain mathematical operations from relational algebra and
relational calculus on the relation such as projection, union and joins etc.
where fields in two different tables take values from the same set, a join
operation can be performed to select related records in the two tables by
matching values in those fields. A description of data in terms of a data
model is called a schema. In relation model, the schema for a relation
specifies its name, the name of each field and the type of each field.
Navigation through relations the represent an M:N relationship is just as
simple as through a 1:M relationship. This leads us to conclude that it is easier to specify how to
manipulate a relational database than a network or hierarchical one. This in turn leads to a query
language for the relational model that is correct, clear, and effective in specifying the required
operations. Unfortunately, the join operation is inherently inefficient and demands a
considerable amount of processing and retrieval of unnecessary data. The structure for the
network and hierarchical model can be implemented efficiently. Such an implementation would
mean that navigating through these databases, though awkward, requires the retrieval of
relatively little unnecessary data.
