Data modeling is a useful thing that is done before working on coding a database. This is to avoid any errors before they occur by keeping the necessary changes before developers start to work.
- Knowledge of Physical Data: To develop a data model you must know the physical data present and stores characteristics.
- No set manipulation language in DBMS
- Has the high impact of failure due to vulnerability when doing approach via database.
Disadvantages of Relational Data Model
- Expensive: Size is a factor as it needs a substantial amount of memory to run efficiently.
- Performance Issue: Slower with large data size
- Complex: Data arranged using common characteristics
- Risk of Data loss: During transfer is higher
- Structure Limitation: Modification is difficult
Disadvantages of Network Data Model
- Complex to Understand: Not user friendly require higher skills.
- Tracking of Pointers: All records are maintained using pointers
- Complex Schema: Limited to structure of the field
- Complex Design
- No automated query optimization
- Not Flexible
Disadvantages of Hierarchical Data Model
- not enough to present all the data between the data element
- Does not follow many to one and many to many relations
- Lack structural independence.
- Data independence.
- Difficult to implement and manage
- Duplicate Data