Comparison of REST and GraphQL web technology performance

Mikuła, Mateusz; Dzieńkowski, Mariusz

doi:10.35784/jcsi.2077

Cited by 3 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Differences in performance for display operations are observed under heavy load conditions. GraphQL has better performance in downloading small amount of data, while REST indicated higher performance in downloading large amount of data [12]. Contradictory results were obtained in [13], migration to GraphQL resulted in improved performance in terms of average number of requests per second and data transfer rate for two-thirds of the applications tested.…”

Section: Introductionmentioning

confidence: 69%

“…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%

“…However, the results are mostly from simulations or execution of simple application development, therefore the results are either inconclusive or inconsistent. Experiments have tested basic operations in network services, i.e., displaying, adding, editing, and deleting data [12]. The performance tests are measured using the JMeter tool.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Lawi¹,

Panggabean²,

Yoshida³

2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 69%

Section: Architectural Difference Of Rest and Graphqlmentioning

confidence: 99%

Section: Performance Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Lawi¹,

Panggabean²,

Yoshida³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…However, the results were mostly from simulations or execution of simple application development; therefore, the results were either inconclusive or inconsistent. Experiments have tested basic operations in network services, i.e., displaying, adding, editing, and deleting data [12]. The performance tests were measured using the JMeter tool.…”

Section: Introductionmentioning

confidence: 99%

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

2021

View full text Add to dashboard Cite

Currently, most middleware application developers have two choices when designing or implementing Application Programming Interface (API) services; i.e., they can either stick with Representational State Transfer (REST) or explore the emerging GraphQL technology. Although REST is widely regarded as the standard method for API development, GraphQL is believed to be revolutionary in overcoming the main drawbacks of REST, especially data-fetching issues. Nevertheless, doubts still remain, as there are no investigations with convincing results in evaluating the performance of the two services. This paper proposes a new research methodology to evaluate the performance of REST and GraphQL API services with two main ideas as novelties. The first novel method is the evaluation of the two services is performed on the real ongoing operation of the management information system, where massive and intensive query transactions take place on a complex database with many relationships. The second is the fair and independent performance evaluation results obtained by distributing client requests and synchronizing the service responses on the two virtually separated parallel execution paths for each API service, respectively. The performance evaluation was investigated using basic measures of QoS (Quality of Services), i.e., response time, throughput, CPU load, and memory usage. We use the term efficiency in comparing the evaluation results to capture differences in their performance measures. The statistical hypothesis parameters test using the two-tails paired t-test, and boxplot visualization was also given to confirm the significance of the comparison results. The results showed REST is still faster up to 50.50% in response time and 37.16% for throughput, while GraphQL is very efficient in resource utilization, i.e., 37.26% for CPU load and 39.74% for 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 are frequently accessed and called by multiple requests.

show abstract

Performance evaluation of microservices communication with REST, GraphQL, and gRPC

Niswar,

Arisandy Safruddin,

Bustamin

et al. 2024

International Journal of Electronics and Telecommunications

View full text Add to dashboard Cite

Microservice architecture has become the design paradigm for creating scalable and maintainable software systems. Selecting the proper communication protocol in microservices is critical to achieving optimal system performance. This study compares the performance of three commonly used API protocols: REST, GraphQL, and gRPC, in microservices architecture. In this study, we established three microservices implemented in three containers and each microservice contained a Redis and MySQL database. We evaluated the performance of these API protocols using two key performance metrics: response time and CPU Utilization. This study performs two distinct data retrieval: fetching flat data and fetching nested data, with a number of requests ranging from 100 to 500 requests. The experimental results indicate that gRPC has a faster response time, followed by REST and GraphQL. Moreover, GraphQL shows higher CPU Utilization compared to gRPC and REST. The experimental results provide insight for developers and architects seeking to optimize their microservices communication protocols for specific use cases and workloads.

show abstract

Comparison of REST and GraphQL web technology performance

Cited by 3 publications

References 3 publications

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

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

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

Performance evaluation of microservices communication with REST, GraphQL, and gRPC

Contact Info

Product

Resources

About