After carrying out the conceptual design of a database, it is necessary to translate it into a logical data model.
The best known and used models are:
Hierarchical data model
This model uses trees for the logical representation of data. This tree is made up of elements called nodes. The highest level of the tree is called the root. Each node represents a record with its corresponding fields.
The graphic representation of this model is done by creating an inverted tree, the different levels are linked by relationships.
In this model, only 1:M relationships can be represented, so it has several drawbacks:
- N:M ratios are not supported
- A child segment cannot have more than one parent.
- More than one relationship between two segments is not allowed.
- To access any segment it is necessary to start with the root segment
- The tree must be traversed in the designated order.
Network data model
In this model the entities are represented as nodes and their relationships are the lines that join them. In this structure any component can be related to any other.
Unlike the hierarchical model, in this model, a child can have multiple parents.
The basic concepts in the network model are:
- The record type, which represents a node.
- Element, which is a data field.
- Data aggregate, which defines a named dataset.
This data model allows us to represent N:M relationships
relational data model
This model is currently the most widely used since it uses two-dimensional tables for the logical representation of data and their relationships.
Some of its main characteristics are:
- It can be understood and used by any user.
- It allows to extend the conceptual scheme without modifying the management applications.
- Users do not need to know where the data is physically located.
The main element of this model is the relationship that is represented by a table.
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