Our journey begins with a robust backend API, leveraging MongoDB as a data storage layer. TypeScript’s embrace of interfaces and contracts allowed for a structured and reliable codebase. The use of design patterns—specifically, the repository pattern for data abstraction and the service pattern for encapsulating business logic—ensured a well-organised architecture.
MongoDB has been chosen as a storage layer for several reasons:
Flexible schema: MongoDB uses a flexible schema design (NoSQL) where documents in a collection don’t need to have a uniform structure. This flexibility is advantageous when dealing with evolving data models.
Scalability: It’s designed to scale horizontally by adding more machines to the database, allowing it to handle large volumes of data and high traffic loads.
Performance: Its ability to store related data in a single document and support for embedded data models can enhance query performance. Additionally, it supports indexing for faster queries.
JSON-like documents: MongoDB stores data in a format similar to JSON, which is often more natural for developers and can simplify data integration with applications.
Replication and high availability: It offers built-in replication, ensuring data redundancy and high availability in case of server failures.
Automatic sharding: MongoDB can automatically partition data across multiple servers, allowing for efficient distribution and scaling of data.
However, it’s important to note that while MongoDB has these advantages, it might not be the best choice for every use case. Factors such as specific data requirements, transactional needs and the nature of the application should be considered when choosing a storage layer.