* Data Models: A data model is a collection of conceptual tools for describing data, data-relationships, data cementics and consistency constraints. There are these groups of data model (1) Object-based logical model. (2) Record-based logical model. (3) Physical data model.
In a record-based logical model the database consist of fixed format records of several types. Each record has a fixed number of fields or attributes and each fields has a fixed length. This is in contrast to the object based logical model. Example of record based models are (1) Relational model. (2) Network model. (3) Hierarchical model.
(1)Relational model: It was first discovered by E.F. codd in 1970. The relational model represent relational ship among data by collection of table, each table has number of columns with unique name. a relational data base is a collection of tables called ‘relation’. Each row of the tables corresponds to a single records from the database. A table row or record is called tuple. The columns of table break each tuple in two distinct sections and each section correspond to the fields within a record called attributes. A fields or attribute has a name. Attribute name must be unique within a relation. The relational data model does not a have a predefined set of relationships between data records. The relational data model used as a product that generates an extract control on our data. For ex:
In above table the first column (attribute), student Id uniquely identified in a table. Therefore it can use as a primary key in a relational model.
Advantages: (1) query language allows performing any operation. The relational query language gives a set of commands that allows us to perform any number operations. (2) No necessity of learning inner structure of database. The relational database is in the form of table. So that only the names of relations where atoms are stored is to be know while designing database.
Disadvantage: (1) query languages consume processing time and memory. (2) Data must be related to act upon.
(2) Network model: The network structure represents more complex logical relationship. It allows many to many relationships among records. The network model allows entry into a data base at multiple points. The network model is similar to the hierarchical data model accepts that it records are not limited to only one superior. That is a records may have many superior records and many subordinate records. It is also possible that a record subordinate is link to the records superior. A group of interconnected nodes is called network. A subway map is a good example of network. In the network data model the nodes are records and connections are relationship. Any hierarchical database can be implemented as a network database management system. A network system allows a given entity to have any number of superiors as well as any number of subordinates. A multiple pointers, with a link node record may represent a connection between two entities.
Advantages: (1) It allows many to many relationship among record. (2) It is flexible in representing relationships.
Disadvantages: (1) Required knowledge of data structure. (2) Not easy add relationships to an existing database.
(3) Hierarchical model: DBMS used hierarchical or tree structure to represent the relationship among entities. Multiple records of a particular type belong to a single record of another type higher in hierarchy parent record can have several children records, but child can have only one parent. The hierarchical database model maintains records in groups of tree structures called forests. The pointer that connects the record represents the relationship between records. All relationships are one to many. Each record has one superior record and may have any number of subordinate records. Each record in the hierarchy has a superior record. A record is accessed through the records that are superior to it in the hierarchy i.e. to access a record in the hierarchy, a path must be found from the root to the record.
Advantages: (1) the structure is top down in nature makes programming efficient. (2) Well suited for modeling hierarchical data.
Disadvantages: (1) Difficult to insert subordinate records without superior records. (2) Deleting superior deletes subordinates.
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