In programming languages, operating system designs, and database management systems, different objects and classes are stored with an association between the objects. Both Aggregation and Composition are used to describe this relationship between the objects for storing and retrieving the datasets more efficiently, by reducing the complexities of time and space.
Aggregation vs Composition
The main difference between Aggregation and Composition is that Aggregation describes the association between the objects that do depend on each other for their creation. Whereas Composition describes the objects that have a direct dependence on each other for their creation and function. In this case, one object has ownership over the other.
Aggregation is an association between two datasets, such as classes or objects, where the objects involved do not have a direct dependence on each other for their creation or function. Thus the manipulation of one object does not alter the status of the other object. This association allows changes to be made without loss.
Composition is a special type of Aggregation and it describes the relationship between two datasets, where the objects or classes involved are directly dependent on each other for their creation, storage, function, and so on. Thus, any modification to one of the datasets directly impacts the other dataset.
Comparison Table Between Aggregation and Composition
|Parameters of Comparison||Aggregation||Composition|
|Definition||Aggregation is a type of association without the dependence of objects on each other||Composition is an association with the dependence of objects on each other|
|Relationship||There is an indirect relationship between the datasets||The parent-child relationship between the datasets|
|UML symbol||Aggregation is denoted with an empty diamond||Composition is denoted with a filled diamond|
|Modification||Modification of one object does not alter the other object||Modification of one object alters the data on the other object|
|Association strength||It is a weak association||It is a strong association|
What is Aggregation?
Aggregation is a type of association or relationship between two datasets such as classes, objects, and so on. The association is made to group the datasets that have similarities together.
In this type of association, the objects or classes do not have a direct relationship. The datasets have a “Has-A” relationship.
This implies that the datasets do not depend on each other for their creation, storage, or any function or operation. This is the key benefit of using this form of association for storing similar datasets.
As the objects and classes do not have a direct dependence on each other, any modification or alteration made to one of the objects or classes does not alter or modify the contents of the data stored in the other dataset.
This makes it possible for destroying one of the datasets in aggregation without having to worry about the data stored in the other dataset.
Because of this property of the Aggregation relationship, it is mostly used in testing environments where the data has to be modified constantly. Due to the “Has-A” relationship between the aggregated objects, the data is not destroyed in the other datasets.
For UML representation, an empty diamond symbol is used to specify the Aggregation relationship.
What is Composition?
Composition is a type of relationship between datasets and is mostly used in database management systems and in designing operating systems. The datasets may include objects, classes, and so on.
The composition creates a relationship between datasets which is more direct than Aggregation. Thus the objects and classes are directly related to each other during the creation of the datasets.
As the objects and classes are directly related, they depend on each other for their creation, storage, and any operation or function.
The relationship is represented sometimes as a “Parent-child” relationship or “owner” relationship, where one dataset is the owner of the other dataset.
The major drawback of using this type of relationship is that when one of the objects or classes is altered or modified, the change is reflected on the other dataset and the data contained in the dataset is also modified.
This has to be noted while working with such datasets as if one of the datasets is destroyed or deleted, the other dataset which is in association with that dataset also gets destroyed.
But the data is stored more securely when using a composition relationship between the objects or classes. For UML representation of a Composition type association, a filled diamond is used.
Main Differences Between Aggregation and Composition
- Aggregation is an association of datasets, where the datasets do not depend on each other. Composition is also a type of association, but the datasets depend on each other.
- In Aggregation there is an indirect relationship between the datasets. In Composition there is a direct relationship between the datasets.
- For UML representation, Aggregation is denoted by an empty diamond, whereas Composition is represented by a filled diamond.
- In an Aggregation type association, any modifications made to one of the objects involved in the association does not alter the data present in the other datasets. In Composition type association, any modification made to one of the datasets is reflected in the other datasets involved in the association.
- Aggregation is weaker type of association than Composition. Data is more securely stored in a composition type association.
Datasets are required for storing data more efficiently when there is some similarity between the data involved. Thus while making database management systems different types of dataset associations are made to reflect the relationship between datasets.
Both Aggregation and Composition are types of associations that reflect the relationship between the data involved.
Aggregation is not a direct relationship and the data involved in this type of association does not depend on each other for their creation and function.
Composition is a direct type of association and the relationship between the data involved is sometimes represented as a “Parent-Child” representation.
Thus Composition is a stronger association than Aggregation, but the dependence of datasets has to be noted while working with this type of association.