Explain the three data models namely relational, network and hierarchical and evaluate their relative advantages and disadvantages.
Hierarchical Model: In hierarchical model, data elements are linked to one another by links. Records are arranged in a top-down structure which resembles a tree or genealogy chart. The top node is known as the root, the bottom nodes are known as leaves, and intermediate nodes have one parent node and various child nodes. The root can have any number of child nodes other than a child node can have only one parent node. Data are associated in a nested, one-to-many set of relationships, although many-to-many relationship cannot be in a straight line expressed.
A child record occurrence must have a parent record occurrence; deleting a parent record occurrence needs deleting all its child record occurrences.
A network data model can be regarded as an extended create of the hierarchical model; the principle distinction among the two being which in a hierarchical model, a child record has precisely one parent while in network model, a child record can have any number of parents. It might have zero also.
Data in the network model is represented through collection of records and relationship between data is represented through links, which can be viewed, as pointers. The records in the database are organized as collection of arbitrary graphs that permit to have one-to- many as well as many-to-many relationship is a collection of data items that can be retrieved from a database or that can be stored within a database as an undivided object.
Therefore, A DBMS may STORE, DELETE or MODIFY records inside a database. In this way, a number of records inside a network database are dynamically changed. The network model can be graphically represented as follows:
A labeled rectangle represents the corresponding entity or record type. An arrow represents the set type, that denotes the relationship among the owner record type and member record. The arrow direction is from the owner record category to the member record type.
A labeled rectangle represents the corresponding entity or record type. An arrow represents the set type, that denotes the relationship among the owner record type and member record. The arrow direction is from the owner record elements to the member record type.
Every many to many relationship is handled through introducing a new record type to represent the relationship wherein the attributes, if any, of the relationship are stored. We while create two symmetrical 1:M sets along with the member within each of the sets being the latest introduced record type. In this model, the relationships as well as the navigation by the database are predefined at database creation time.
In relational model the data and the relations between them are represented through a collection of tables. A tables is a collection of records and every record in a table contains the similar fields. The attractiveness of the relational approach arouses from the simplicity in the data organization and the availability of capably simple to extremely powerful query languages. The relational model is based on a technique known as "Normalization" proposed by E.F. Codd.
This model decreases the complexity of the Network and Hierarchical Models. This model uses the certain mathematical operations from relational algebra and relational calculus on the relation like as projection, union and joins etc. where as fields in two different tables take values from the similar set, a join operation could be performed to select associated records in the two tables through matching values in those fields. A description of data in terms of a data model is known as 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 only as simple as by a 1:M relationship. This leads us to conclude in which it is simpler 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 effectual 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 in which navigating through these databases, by awkward, requires the retrieval of comparatively little unnecessary data.