Comparative Analysis of Pipeline Architecture, Resource Deployment, and Configuration for Cassandra API-Compatible Databases: ScyllaDB vs. Cassandra

Iryna Tyshchenko; Rand Kouatly; Talha Ali Khan

doi:10.2478/acss-2025-0019

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Comparative Analysis of Pipeline Architecture, Resource Deployment, and Configuration for Cassandra API-Compatible Databases: ScyllaDB vs. Cassandra

Applied Computer Systems

Volume 30 (2025): Issue 1 (January 2025)

By: Iryna Tyshchenko, Rand Kouatly and Talha Ali Khan

Open Access

|Dec 2025

Abstract

This work builds a benchmarking pipeline for resource deployment, configuration input, and the evaluation of Cassandra and ScyllaDB performance. It investigates performance under different scenarios, workload types, and internal structures. Insights and future improvements are provided. Analysing comparisons of both databases, there were several notable differences between Cassandra and ScyllaDB. ScyllaDB demonstrated superior performance in production-ready materialized views, global secondary indices, lightweight transactions, change data capture, row-based data cache, and adaptive behaviour to real-world workloads. On the other hand, Cassandra exhibited advantages, such as a well-established size-tiered compaction approach and the ability to leverage existing Java Virtual machine (JVM) tuning techniques.

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Articles in this issue

DOI: https://doi.org/10.2478/acss-2025-0019 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683

Journal RSS Feed

Language: English

Page range: 174 - 186

Submitted on: Apr 15, 2025

Accepted on: Nov 21, 2025

Published on: Dec 12, 2025

Published by: Riga Technical University

In partnership with: Paradigm Publishing Services

Publication frequency: Volume open

Keywords:

Bigdata,

benchmarking,

Cassandra,

ScyllaDb,

YCSB,

AWS,

Related subjects:

Artificial intelligence,

Information technology,

Project management,

Software development

© 2025 Iryna Tyshchenko, Rand Kouatly, Talha Ali Khan, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 30 (2025): Issue 1 (January 2025)