In the evolving landscape of software development, the debate between using REST and GraphQL to build microservices is becoming increasingly relevant. Both technologies have their advocates and critics, but when it comes to the specific needs of microservices architectures, GraphQL emerges as the clear leader. Here’s why.
Understanding RESTful concerns
Popularity versus limitations
While REST has been the common API style for many years, praised for its simplicity and general applicability, its limitations become apparent in the context of microservices. These restrictions include:
- Excessive data retrieval.
- More HTTP requests for related data.
- Complex versioning strategies.
Such issues can hinder the performance and scalability of microservices architectures.
Excessive data retrieval
REST APIs are designed to return a fixed set of data, which often results in excessive fetching. This redundancy is particularly problematic in mobile networks, where each additional byte of data can lead to slower applications and a degraded user experience.
For example:
Imagine we have a REST API endpoint /API/user/userId, which returns the following data for a user:
In scenarios where mobile applications only require specific user information such as name and email address to view a profile, retrieving comprehensive user data is over-retrieval.
This excessive data usage can be costly for users with limited data plans and result in slower app performance and degraded user experience.
Latency and the N+1 problem
Microservices often require data that is distributed across multiple services.
Suppose you have an e-commerce application where the Order domain handles the Product, Customer, Order, and Return entities, and the Inventory domain handles the Product, Inventory, Warehouse, and Shipping entities. A common operation might be to display the order details along with the current inventory status for each product in the order.
Let’s say we have an orders microservice and an inventory microservice to handle orders and inventory.
If a customer placed 3 orders (N=3), and each order contains 4 different products. To display order details along with inventory status for each product, the application first issues 1 order fetch request. Then, for each product in each order, it makes additional requests to the inventory microservice to retrieve inventory information. This results in 1 initial request + 12 subsequent requests (3 orders * 4 products per order), which adds up to 13 API calls. This multiplicative increase in requests leads to higher latency due to multiple round trip times (RTTs) and increased network and server load, which embodies the N+1 problem.
Versioning Challenges
Maintaining a REST API over time involves complex versioning strategies, such as introducing new endpoints or embedding version numbers in the API path. This can lead to bloat and confusion, complicating API development and usage.
Advantage of GraphQL
Domain-centric design
Microservices thrive on domain-driven design, where each service is built around a specific business capability. GraphQL’s schema-centric approach aligns perfectly with this, enabling a more organized and coherent structure for microservices.
Unified scheme
In a microservices architecture, each service can have its own schema, which represents part of the business domain. GraphQL excels by allowing these schemas to be combined or “merged”, presenting a single interface to clients. This means that clients can request data from multiple services in a single request, drastically reducing the complexity and number of network calls.
Solving the N+1 problem
GraphQL’s ability to retrieve data in a single request, regardless of how many underlying services need to be called, directly solves the N+1 problem inherent in REST architectures. This not only improves performance, but also simplifies the data retrieval logic on the client side.
For the N + 1 problem described earlier, if the services support GraphQL, it can be used to retrieve nested data in a single query, effectively solving the N + 1 problem.
Efficiency and performance
By allowing clients to specify exactly what data they need, GraphQL eliminates the overfetching and underfetching problems common in REST APIs. This leads to more efficient data retrieval, reduced bandwidth usage and faster applications, which is especially evident in mobile environments.
In the earlier scenario where mobile applications require only certain user information such as name and email to view a profile, clients may require only name and email.
Simplified versioning
Unlike REST, GraphQL reduces the need for versioning by allowing new fields and types to be added to the schema without affecting existing queries. This forward compatibility means that clients and servers can more easily evolve over time.
GraphQL stands today as a mature technology that addresses specific needs in modern web development that are not fully met by traditional REST APIs. Its design promotes developer efficiency, flexibility and productivity. Looking ahead, the future of GraphQL is bright, with community-driven efforts aimed at addressing its current limitations, particularly around security, performance, and standardization. As these efforts bear fruit, GraphQL adoption is expected to expand, cementing its position as a key technology in the API landscape.