Performance Analysis of GraphQL and RESTful in SIM LP2M of the Hasanuddin University

Hartina, Dewi Ayu; Lawi, Armin; Panggabean, Benny Leonard Enrico

doi:10.1109/eiconcit.2018.8878524

Cited by 12 publications

(11 citation statements)

References 3 publications

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“…GraphQL that uses a single endpoint is more efficient than other APIs that use multiple endpoints, but GraphQL will also be a bit slower to query complex databases and have many relationships in addition to that other APIs are built with multiple endpoints to determine the data returned. This will increase the number of client-server calls to display data to the user and this may result in poorer service performance in Application requirements (Hartina et al, 2018).…”

Section: Graph Query Language (Graphq)mentioning

confidence: 99%

Information System Web Based for Group Randomization of State Defense Education Class using Linear Congruential Method

2022

Nusantara Science and Technology Proceedings

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One of the actual forms of state defense education is through outbound activities. In this context, education is interpreted as a process to humanize humans to become fully human adults. However, the world was shocked by the outbreak of a disease caused by a virus called corona or known as covid-19. Transmission through social contact between humans is difficult to predict and also cannot be avoided so its spread is also very rapid. Therefore, it is necessary to change the outbound state defense education method from conventional activities to offline activities based on the web and automatically computed. The system will replace the conventional process of supervising outbound activities where activities that are usually carried out in groups and simultaneously, will be carried out independently by sending evidence of activities that have been recorded through document files or videos. The results of this study are the Outbound State Defense Group Randomization Information System (SIOBEL) using the Linear Congruent Method (LCM) which helps in creating random groups of students and with the Graph Query Language (Graph-QL) system architecture which can facilitate interface and system developers to exchange data.

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Section: Graph Query Language (Graphq)mentioning

confidence: 99%

Information System Web Based for Group Randomization of State Defense Education Class using Linear Congruential Method

2022

Nusantara Science and Technology Proceedings

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“…Penelitian lain membahas mengenai perbandingan performa antara GraphQL dan REST API pada sistem informasi, penelitian tersebut menyimpulkan bahwa GraphQL dapat menjadi pilihan yang tepat ketika data yang dibutuhkan sering berubah (Hartina, Lawi, & Panggabean, 2018).…”

Section: Pendahuluanunclassified

Implementasi GraphQL Untuk Mengatasi Under-Fetching pada Pengembangan Sistem Informasi Pelacakan Alumni Politeknik Negeri

Firdausi¹,

Hormansyah²,

Ervansyah³

2021

JIP

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Pendistribusian data pada sistem informasi memiliki berbagai macam cara yang digunakan. Diantaranya adalah dengan menggunakan metode REST API. Namun, terdapat beberapa kekurangan yang menjadi masalah pada REST API. Salahsatunya adalah masalah under-fetching, yaitu masalah dimana bagian frontend harus melakukan lebih dari 1 kali request untuk memenuhi kebutuhan data yang diperlukan. Masalah ini dapat diselesaikan dengan menerapkan GraphQL sebagai metode pendistribusian data. Tujuan dari penelitian kali ini adalah untuk membandingkan performa antara sistem informasi dengan REST API dan sistem informasi dengan GraphQL. Studi kasus pada penelitian ini adalah pada pengembangan sistem informasi pelacakan alumni Politeknik Negeri Malang. Hasil penelitian ini berupa perbandingan performa antara sistem informasi dengan metode pendistribusian data REST API dan sistem informasi dengan metode pendistribusian data GraphQL. GraphQL menunjukkan performa yang baik pada jumlah data yang besar dan kompleks, serta ketika terdapat banyak pengguna yang mengakses data dalam waktu yang bersamaan. Sedangkan untuk data yang sederhana dan sistem informasi yang tidak memiliki banyak pengguna yang akan mengakses data secara bersamaan, maka REST API masih lebih unggul.

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“…The REST configuration creates a complicated situation whenever there is a change on the back-end, it will cause an adjustment to the front-end to query the exact endpoint for the desired resource. On the other hand, GraphQL will take some time when the request is handled at a single endpoint to find the right resource [1,3,12,13,16]. Figure 3 illustrates the difference between REST and GraphQL architecture.…”

Section: Architectural Difference Of Rest and Graphqlmentioning

confidence: 99%

“…Meanwhile, web service workload performance is more easily demonstrated through CPU load and memory usage. Obviously, the response time and throughput depend on the workload the web server is experiencing at the time [12,14,16,21]. Therefore, this paper evaluates 4 basic performance measures that clearly distinguish the two technologies based on their natural purpose.…”

Section: Performance Measurementsmentioning

confidence: 99%

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

Lawi¹,

Panggabean²,

Yoshida³

2021

Preprint

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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.

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Performance Analysis of GraphQL and RESTful in SIM LP2M of the Hasanuddin University

Cited by 12 publications

References 3 publications

Information System Web Based for Group Randomization of State Defense Education Class using Linear Congruential Method

Information System Web Based for Group Randomization of State Defense Education Class using Linear Congruential Method

Implementasi GraphQL Untuk Mengatasi Under-Fetching pada Pengembangan Sistem Informasi Pelacakan Alumni Politeknik Negeri

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

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