STREAMLINING API DEVELOPMENT: A COMPARATIVE ANALYSIS OF GRAPHQL AND RESTFUL WEB SERVICES
Keywords:
REST API, GraphQL, Web ServicesAbstract
Modern data-driven apps place a premium on well-structured and efficient interaction with backend APIs. With its enhanced efficiency and greater adaptability, GraphQL quickly became a formidable contender to REST APIs. One of the most well-known GraphQL client libraries, Apollo Client, makes it even easier to communicate with GraphQL services. In order to improve the developer experience and code quality, this article explores how to use the Apollo Client's service models to create strongly typed representations of your GraphQL schema. An alternative to existing methods for dealing with issues related to data access and versioning in representational state transfer APIs, GraphQL is an execution engine and query language for online application programming interfaces (APIs). When it comes to creating or implementing API services, most middleware application developers can choose between two options: After that, you have the option to continue using REST or investigate the emerging GraphQL protocol. Most people agree that REST is the best way to build an API, but GraphQL is thought to be revolutionary because it fixes REST's biggest problems, especially with getting data. But there are still questions because no studies have created strong results when comparing how well the two programs work. Throughput, reaction time, CPU load, and memory consumption are some of the fundamental Quality of Service (QoS) measures that were utilized to examine the performance evaluation. We use the word efficiency to describe how the performance criteria used to compare the evaluations vary. A boxplot visualization was employed to demonstrate the significance of the comparing results, in addition to testing the statistical hypothesis parameters with the two-tails paired t-test. With a response time advantage of up to 50.50 percent and a throughput advantage of 37.16 percent, REST appears to be the quickest method. In contrast, GraphQL uses just 37.26% of the CPU and 39.54% of the memory, demonstrating its remarkable resource efficiency.
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