GraphQL is a powerful technology that can help you create more efficient and flexible APIs for your clients. In this blog, I will explain what the backend for frontend pattern is, why GraphQL is a good fit for it, and how to implement it using Apollo GraphQL.
What is the backend for frontend pattern?
The backend for frontend (BFF) pattern is a design approach that aims to solve the problem of having different clients (such as web, mobile, or desktop) that need to interact with a single, general-purpose API. A general-purpose API may not be able to meet the specific needs and expectations of each client, resulting in over-fetching or under-fetching of data, increased network traffic, slower performance, and complex logic on the client side.
A BFF is a data transformation layer that sits between a client and the API, and provides a tailored interface for each client to fetch only the data it needs, in the shape it expects. A BFF can also handle authentication, authorization, caching, logging, and other cross-cutting concerns that are common to all clients. By using a BFF, you can improve the user experience of your application, reduce the load on your server, and simplify the development and maintenance of your client code.
Why use GraphQL for BFFs?
GraphQL is a query language for APIs and a runtime for fulfilling queries with existing data sources. GraphQL allows clients to specify what data they want and how they want it, and returns exactly that. GraphQL also allows servers to define the data they can provide using a schema language. This makes GraphQL a perfect technology for building BFFs, as it enables the following benefits:
Declarative: Clients can declare what data they need using GraphQL queries, without worrying about how the data is fetched or transformed. This makes the client code more readable and maintainable.
Flexible: Servers can expose any data source (such as databases, REST APIs, microservices, etc.) as a GraphQL schema, and use resolvers to fetch and resolve the data. This makes the server code more modular and adaptable.
Efficient: GraphQL queries can fetch only the data that is needed by the client, avoiding over-fetching or under-fetching. GraphQL also supports features such as batching, caching, and subscriptions to optimize network performance and reduce latency.
Introspective: GraphQL schemas are self-documenting and can be explored using tools such as GraphiQL or Apollo Studio. This makes it easy to discover and understand the available data and operations.
