In a scenario where an application requires transactions across multiple data models, how does the Unit of Work pattern enhance data consistency?
- It enables parallel processing of data operations across different data models, enhancing scalability.
- It improves performance by caching data from multiple data models, reducing database round-trips.
- It simplifies the codebase by abstracting the data access layer, making it easier to manage and maintain.
- It tracks changes across multiple data models and ensures that either all changes are committed or none, preserving data integrity.
The Unit of Work pattern helps maintain data consistency by tracking changes across multiple data models within a single transaction scope. This ensures that either all changes are committed successfully or none of them, preventing partial updates that could lead to data inconsistencies. This pattern promotes atomicity and data integrity in complex transactions involving multiple entities.
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