Efficiency comparison of message brokers

Sebastian Dyjach

sebastian.dyjach@pollub.edu.pl
Lublin University of Technology (Poland)

Małgorzata Plechawska-Wójcik


Lublin University of Technology (Poland)

Abstract

The aim of the article is to compare three main brokers used in the development of web applications: RabbitMQ, Apache Kafka and Apache Pulsar. To conduct the research, a custom application was created to compare two key metrics in the context of message queue performance. These metrics are: latency and number of processed messages per second. The conducted experiments showed that in scenarios requiring processing of backlogged messages by the broker and in cases of minimizing the impact of the SSL protocol on broker performance, Apache Pulsar proved to be the best solu­tion. In the scenario examining message delivery delays, RabbitMQ turned out to be the best tool, while in the case of examining the stability of message processing in real-time, the best results were achieved with Apache Kafka.


Keywords:

Apache Kafka, Apache Pulsar, message broker, RabbitMQ

Oficjalna dokumentacja narzędzia Spring Boot, https://docs.spring.io/spring-boot/docs/current/reference/html, [21.03.2024].
  Google Scholar

Dokumentacja platformy spring-cloud-binder, https://cloud.spring.io/spring-cloud-stream/multi/multi_spring-cloud-stream-overview-binders.html, [21.03.2024].
  Google Scholar

G. Fu, Y. Zhang, G. Yu, A Fair Comparison of Message Queuing Systems, IEEE Access 9 (2020) 421-431, https://dx.doi.org/10.1109/ACCESS.2020.3046503.
  Google Scholar

Magnoni, Luca. Modern messaging for distributed systems. Journal of Physics: Conference Series., IOP Publishing (2015) 2-6.
  Google Scholar

B. Singh., B. H. Chaitra. Comprehensive Review of Stream Processing Tools. International Research Journal of Engineering and Tech¬nology 7(5) (2020) 3537-3540.
  Google Scholar

K. Sowmya, T. Sharvari, A study on Modern Mes¬saging Systems - Kafka, RabbitMQ and NATS Stream¬ing, CoRR abs/1912.03715 (2019) 2-5.
  Google Scholar

M. Rokin, S. Hossain, M. Ashfakur, Benchmarking Message Queues, Department of Computer Science, Bay-lor University (2023) 298-312, https://doi.org/10.3390/telecom4020018.
  Google Scholar

Oficjalna dokumentacja OpenMessaging Benchmark Framework, https://openmessaging.cloud/docs, [20.03.2024].
  Google Scholar

P. Jeba, P. Marca, J. Arockia. Comparison of JMS Products, International Journal of Scientific Research in Computer Science (2018) 190-193, https://doi.org/10.32628/CSEIT183858.
  Google Scholar

T. E. Pereira, R. de Araújo Souza, Performance analysis between Apache Kafka and Rab¬bitMQ, UFCG (2020) 5-11.
  Google Scholar

Oficjalna dokumentacja narzędzia Apache Kafka, https://kafka.apache.org/documentation, [22.03.2024].
  Google Scholar

Platforma Linkedin, https://www.linkedin.com, [01.04.2024].
  Google Scholar

V. E. Balas, L.C Jain, Replication in Raft vs Apache Zookeeper, Proceedings of the 9th International Workshop Soft Computing Applications (2020) 426-436, https://doi.org/10.1007/978-3-031-23636-5.
  Google Scholar

Oficjalna strona narzędzia RabbitMQ, https://www.rabbitmq.com, [23.03.2024].
  Google Scholar

Oficjalna dokumentacja narzędzia Apache Pulsar https://pulsar.apache.org/docs, [23.03.2024].
  Google Scholar

A. Anjum, I. Odun-Ayo, Cloud multi-tenancy: Issues and developments, Proceedings of the 10th International Con-ference on Utility and Cloud Computing (2017) 209-214, https://doi.org/10.1145/3147234.3148095.
  Google Scholar

Dokumentacja firmy Oracle dotycząca tworzenia keystore oraz truststore formatem JKS, https://docs.oracle.com/cd/E19509-01/820-3503/ggfen/index.html, [26.03.2024].
  Google Scholar

Download


Published
2024-06-30

Cited by

Dyjach, S., & Plechawska-Wójcik, M. (2024). Efficiency comparison of message brokers. Journal of Computer Sciences Institute, 31, 116–123. https://doi.org/10.35784/jcsi.6084

Authors

Sebastian Dyjach 
sebastian.dyjach@pollub.edu.pl
Lublin University of Technology Poland

Authors

Małgorzata Plechawska-Wójcik 

Lublin University of Technology Poland

Statistics

Abstract views: 148
PDF downloads: 151


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.