Title: Comparative analysis of real-time messages in big data pipeline architecture

Authors: Thandar Aung; Hla Yin Min; Aung Htein Maw

Addresses: University of Information Technology, Parami Road, Universities' Hlaing Campus, Ward (12), Hlaing Township, Yangon, Myanmar ' University of Information Technology, Parami Road, Universities' Hlaing Campus, Ward (12), Hlaing Township, Yangon, Myanmar ' University of Information Technology, Parami Road, Universities' Hlaing Campus, Ward (12), Hlaing Township, Yangon, Myanmar

Abstract: Nowadays, real-time messaging system is the essential thing in enabling time-critical decision making in many applications where it is important to deal with real-time requirements and reliability requirements simultaneously. For dependability reasons, we intend to maximise the reliability requirement of the real-time messaging system. To develop a real-time messaging system, we create real-time big data pipeline by using Apache Kafka and Apache Storm. This paper focuses on analysing the performance of producer and consumer in Apache Kafka processing. Apache Kafka is the most popular framework used to ingest the data streams into the processing platforms. The comparative analysis of Kafka processing is more efficient to get reliable data on the pipeline architecture. Then, the experiment will be conducted the processing time in the performance of the producer and consumer on various partitions and many servers. The performance analysis of Kafka can impact on messaging systems in real-time big data pipeline architecture.

Keywords: messaging; real-time processing; Apache Kafka; Apache Storm; messaging system; performance analysis; big data pipeline.

DOI: 10.1504/IJHPCN.2019.106108

International Journal of High Performance Computing and Networking, 2019 Vol.15 No.3/4, pp.191 - 201

Received: 22 Mar 2019
Accepted: 21 Aug 2019
Published online: 30 Mar 2020 *

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