Data models include hierarchical data models, mesh data models, and ( ).

Data models include hierarchical data model, mesh data model and relational data model, which are related as follows:

1. Hierarchical data model: Hierarchical data model is a tree-structured model in which each node represents a set of entities. The relationships of entities are represented by pointers from child nodes to parent nodes. It is easy to understand and interpret and has a simple structure. However, it cannot directly express many-to-many relationships and has limited scalability. Applicable to organizational structure, family tree, file system and other scenarios.

2, mesh data model: mesh data model, nodes represent entities, edges represent relationships between entities. This model can express many-to-many relationships, but the structure is complex, management and maintenance costs are high. Can express complex relationships, but the structure is complex, management and maintenance costs are high. It is suitable for scenarios that need to express complex relationships but do not have high real-time requirements, such as certain enterprise management systems.

3, relational data model: relational data model based on mathematical set theory, using two-dimensional table form to organize data. Each row represents a record, and each column represents an attribute or field. Clear structure, high query efficiency, support for complex query operations. However, it lacks support for unstructured data. Widely used in database systems, information systems, software engineering and other fields.

Related Knowledge of Data Model

1, the basic concept of data model: data model is a kind of abstraction of the characteristics of the data in the real world, which includes three parts, namely, data structure, data operation and data constraints. Data structure describes the organization and type of data, data operations define what operations can be performed on the data, and data constraints limit the range of values and relationships of the data.

2, data model classification: according to the different application areas, data model can be divided into conceptual model, logical model and physical model. Conceptual model is mainly used for database design, such as entity-relationship model; logical model is the core of the database management system, such as the relational model; physical model describes the way data are stored in the computer system and access methods.

3, the development of the data model: with the continuous progress of technology, the data model is also evolving. From the earliest relational model to the later hierarchical model, mesh model, object-oriented model, etc., each model has its applicable scenarios and advantages and disadvantages. Understanding the characteristics of different data models helps to better select and use data models.