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PL
W artykule przedstawiono porównanie wydajności trzech sposobów realizacji interfejsów programistycznych stosowa-nych w aplikacjach webowych – REST, GraphQL oraz gRPC. Na potrzeby badań opracowano trzy aplikacje, które zostały wykonane w każdej ze wskazanych technologii i o takich samych funkcjonalnościach. Aplikacje wykorzystano do testów wydajnościowych, przeprowadzonych z użyciem narzędzia k6. Aplikacje zastosowano do zmierzenia czasu wykonania, wydajności i objętości przetwarzanych danych podczas operacji wyświetlania oraz dodawania rekordów. Uzyskane wyniki pozwoliły na sformułowanie wniosku, że najlepszym interfejsem pod względem wydajności (mierzonych jako liczba wykonywanych transakcji na sekundę) oraz czasu odpowiedzi serwera jest REST. Natomiast pod względem najmniejszej objętości danych, najlepszym wyborem jest gRPC.
EN
The article presents a comparison of the performance of three ways of implementing programming interfaces used in web applications - REST, GraphQL and gRPC. For the purposes of the research, three applications were developed, which were made in each of the indicated technologies and with the same functionalities. The applications were used for performance tests carried out with the use of the k6 tool. The applications are used to measure the execution time, performance and volume of processed data during display and adding operations. The obtained results allowed for the conclusion that the best interface in terms of performance (measured as the number of transactions per second) and server response time is REST. However, in terms of the smallest data volume, gRPC is the best choice.
2
Content available remote Comparative Review of Selected Internet Communication Protocols
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EN
With a large variety of communication methods and protocols, many software architects face the problem of choosing the best way for services to share information. For communication technology to be functional and practical, it should enable developers to define a complete set of CRUD methods for the processed data. The research team compared this paper’s most commonly used data transfer protocols and concepts: REST, WebSocket, gRPC GraphQL and SOAP. A set of web servers was implemented in Python, each using one of the examined technologies. Then, the team performed an automated benchmark measuring time and data transfer overhead for a set of defined operations: creating an entity, retrieving a list of 100 entities and fetching details of one entity. Tests were designed to avoid the results being interfered with by database connection or docker-compose environment characteristics. The research team has concluded that gRPC was the most efficient and reliable data transfer method. On the other hand, GraphQL turned out to be the slowest communication method of all. Moreover, its server and client libraries caused the most problems with proper usage in a web server. SOAP did not participate in benchmarking due to limited compatibility with Python and a lack of popularity in modern web solutions.
EN
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.
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