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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.