Your data model is not an API: what you need to know in 2023

APIs should be treated as products rather than mere extensions of data models, emphasizing the need to consider API design separately to avoid exposing internal implementation details that can lead to frequent changes and performance issues for consumers. While data models standardize how information is stored and retrieved, APIs define how users interact with applications, necessitating a focus on modularization and loose coupling to maintain stability and ease of integration. The common practice of directly mapping data models to APIs, driven by familiarity and speed, often burdens consumers with adapting to changes and dealing with inefficient data access, underscoring the importance of designing APIs that are consumer-centric, hiding internal complexities, and offering coherent capabilities. By applying software design principles, such as high cohesion and modularity, teams can create APIs that maintain a stable contract with consumers, enabling seamless integration despite underlying changes.