Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Evaluating GraphQL and REST API Services Performance in a Massive and Intensive Accessible Information System

Version 1 : Received: 20 September 2021 / Approved: 22 September 2021 / Online: 22 September 2021 (13:29:56 CEST)

A peer-reviewed article of this Preprint also exists.

Lawi, A.; Panggabean, B.L.E.; Yoshida, T. Evaluating GraphQL and REST API Services Performance in a Massive and Intensive Accessible Information System. Computers 2021, 10, 138. Lawi, A.; Panggabean, B.L.E.; Yoshida, T. Evaluating GraphQL and REST API Services Performance in a Massive and Intensive Accessible Information System. Computers 2021, 10, 138.

Abstract

Currently, most middleware application developers have two choices when designing or implementing API services: They can either stick with REST or explore the emerging GraphQL technology. Although REST is widely considered the standard method for API development, GraphQL is believed to overcome the main drawbacks of REST, especially data fetching issues. Yet, doubts remain as there are no experimental studies with convincing results to evaluate the performance of the two services. In this paper, we propose a research methodology to evaluate the performance of REST and GraphQL API services, which includes two main contributions. The first contribution is that the performance evaluation of the two services is conducted in the real operation of a massive and intensively accessible management information system. The second contribution is the fair and independent performance evaluation results obtained for both API services. The performance evaluation was studied using basic measures of QoS, including response time, throughput, CPU load, and memory usage. The results show that REST is still faster in response time and throughput, while GraphQL is very efficient in resource utilization, i.e., CPU load and memory utilization. Therefore, GraphQL is the right choice when data requirements change frequently and resource utilization is the most important consideration. REST is used when some data is frequently accessed called by multiple requests.

Keywords

information systems; middleware applications; Application Programming Interfaces (APIs); web services; Quality of Services (QoS); performance evaluation

Subject

Computer Science and Mathematics, Information Systems

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