Distributed Streaming Storage Performance Benchmarking: Kafka and Pravega
Sanjay Kumar N V1, Keshava Munegowda2

1Mr. Sanjay Kumar N V, Associate Professor, Department of CSE, Kalpataru Institute of Technology, Tiptur (Karnataka), India.

2Dr. Keshava Munegowda, Consultant, Pravega Bangalore, (Karnataka), India.

Manuscript received on 03 December 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 31 December 2019 | PP: 1-8 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10011292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1001.1292S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The performance benchmarking tool for a distributed streaming storage system should be targeted toachieve maximum possible throughput from the streaming storage system by thrusting data massively. This paper details the design and implementation of high-performance benchmark tool for Kafka and Pravega streaming storage systems. The benchmark tool presented in this paper supports multiple writers and readers. The Pravega streaming storage is evaluated against Kafka with respect to performance.

Keywords: Benchmarking, Big Data, Concurrency, Distributed Systems, Events, Kafka, Latency, Open Messaging, Performance, Pravega, Streams, Storage, Throughput.
Scope of the Article: Storage-Area Networks