The Repository Design Pattern is a software design pattern that separates the logic that retrieves data from the underlying data storage mechanism. It is an abstraction layer that provides a clean interface for the application code to interact with while hiding the implementation details of the data access layer.
In the Repository Design Pattern, the application code interacts with the repository interface, which defines a set of methods for performing common CRUD (Create, Read, Update, Delete) operations on the data. The repository interface is implemented by a concrete repository class, which provides the actual implementation of the data access logic. The concrete repository class interacts with the underlying data storage mechanism, such as a database, to retrieve or store data.
The repository pattern separates the data access logic and maps it to the business entities in the business logic. Communication between the data access logic and the business logic is done through interfaces.
In the Repository Design Pattern architecture, several key components work together to provide a clean interface for the application code to interact with the data storage layer.
Business Logic: The business logic component defines the business entities and the persistent queries that the application needs to perform on the data. The business entities represent the objects that the application needs to work with, and the persistent queries define the operations that the application needs to perform on the data, such as retrieving, updating, or deleting records.
Data Mapper: The Data Mapper is responsible for mapping the business entities to the data storage layer. It converts the data from the data source format into the business entity format and vice versa. The Data Mapper also provides a layer of abstraction that shields the application from the implementation details of the data storage layer.
Query Object: The Query Object is responsible for encapsulating the query logic that the application needs to perform on the data. It provides a clean and modular way to define and execute complex queries on the data. The Query Object also helps to improve the maintainability and readability of the application code by encapsulating the query logic.
Data Source: The Data Source is the underlying data storage mechanism, such as a database or a file system. The Data Source provides the data that the application needs to work with and the Data Mapper translates the data between the Data Source format and the Business Entity format.
Repository Design Pattern provides an abstraction layer between the application code and the data access layer, making it easier to switch between different data storage technologies or databases. The main operations that are typically performed in the Repository Design Pattern include:
Create: This operation is used to create new entities in the data store. The repository typically receives a data object representing the new entity to be created and persists it to the data store.
Read: This operation is used to retrieve data from the data store. The repository typically receives a query object that defines the criteria for the data to be retrieved and returns a collection of entities that match the criteria.
Update: This operation is used to modify existing entities in the data store. The repository typically receives a data object representing the modified entity and updates the corresponding record in the data store.
Delete: This operation is used to remove entities from the data store. The repository typically receives a data object representing the entity to be deleted and removes the corresponding record from the data store.
Query: This operation is used to retrieve data from the data store based on a specific set of criteria. The repository typically receives a query object that defines the criteria for the data to be retrieved and returns a collection of entities that match the criteria.
Aggregate: This operation is used to perform calculations or statistical operations on the data stored in the data store. The repository typically receives a query object that defines the calculation or statistical operation to be performed and returns the result of the operation.
In addition to these basic operations, some repositories may also support more advanced features such as paging, sorting, and filtering of data. The exact set of operations supported by a repository depends on the specific requirements of the application and the data store being used.
Advantages:
Database access logic and domain logic can be tested separately with this pattern.
Domain-driven development is easier.
Clean, maintainable, and reusable code
It reduces the redundancy of code; a generic repository is a better solution than a normal repository pattern to reduce code duplication.
With this pattern, it is easy to maintain the centralized data access logic.
DRY (Don’t Repeat Yourself) design, the code to query and fetch data from a data source, commands for updates (update, deletes) are not repeated.
By using the Repository design pattern, you can hide the details of how the data is eventually stored or retrieved to and from the data store (the data store can be a database, an XML file, etc)
Provides a flexible architecture.
Disadvantages:
An extra layer of abstraction - Due to another layer of abstraction a certain level of complexity makes it overkill for small applications.
With repository patterns, it requires creating a new repository for each entity.
The repository pattern does not decouple the data access from the data store, yes that is correct and it breaks here a clean coding approach.