Database Structure
Three traditional approaches have been implemented commercially to organize records
and their relationships logically: These logical organization approaches are known as database structure. The three traditional database structures are the;
1. Hierarchical Database Structure
2. Network Database Structure
3. Relational Database Structure
1. Hierarchical Database Structure:
In a hierarchical dataset, records are logically organized into a hierarchy of relationships. A hierarchically structured database is arranged logically in an inverted tree pattern.
All records in a hierarchy are called nodes. Each node is related to the others in a parent-child relationship. Each parent may have one or more child record, but-no child record may have more than one parent record. Thus, hierarchical data structure implements one-to-one and one-to-many relationships.
Top parent record in the hierarchy is called the root record. Records that "own" other records are called parent records. There can be many levels of node records in a database.
Hierarchically structured databases are less flexible than other database structures because the hierarchy of records must be determined and implemented before a search can be conducted.
On the plus side, a hierarchical database management system usually processes structured, day-to-day operational data rapidly. In fact, the hierarchy of records is usually specifically organized to maximize the speed with which large operations such as payroll or sales invoices are processed.
2. Network Database Structure:
Another database structure is a net-work. A network database structure views all records in sets. Each set is composed of an owner record and one or more member records. This is analogous to the hierarchy's parent-child relationship. Thus, the network model implements the one-to-one and the one-to-many record structures.
Unlike hierarchical data structure that require specific entrance points to find records in a hierarchy, network data structures can by entered and traversed more flexibly. However, like the hierarchical data mode, the network model requires that records relationships be established in advance because these relationships are physically implemented by the DBMS when allocating storage space on disk. The requirement of established sets means that records processing for regular reports is likely to be rapid.
Record relationships are usually structured to fit the processing needs of large batch reports. However, ad hoc requests for data, requiring record relationships not established in the data mode, may not be very rapid at all, and in some case, they may not be possible.
3. Relational Database Structure
A third database structure is relational model. A relational database is structured into a series of two-dimensional tables. Because many users often work with tabular financial data, it is easy for most of them to understand the structure used in a relational database.
Relational databases allow the users flexibility in conducting database queries and creating reports. Queries can be made and new tables created using all or part of the data from one or more tables. The links between data elements in a relational database do not need to be made explicit at the time the database is created new links can be structured at any time. Thus, the relational database structure is more flexible than hierarchical or network database structures and provide a rich opportunity for ad hoc reports and queries. However, because the do not specify the relationship among data element in advance, relational databases do not process large batch applications with the speed of hierarchical or network databases.
by: Rashid Javed
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