Performance Analysis of NoSQL Databases for Healthcare Applications: A Benchmarking Study of MongoDB, Cassandra and Couchbase

Abstract

Introduction: The burgeoning volume of healthcare data necessitates real-time processing capabilities, driving a surge in demand for scalable and efficient database solutions.

Objectives: This paper presents a comprehensive performance evaluation of three prominent NoSQL databases—MongoDB, Cassandra, and Couchbase—tailored for healthcare applications. We benchmark these databases across key performance metrics, including read and write throughput, latency, scalability, and fault tolerance, utilizing a realistic healthcare dataset - Medical Information Mart for Intensive Care III (MIMIC-III). Our analysis aims to elucidate the distinct strengths and weaknesses of each database in handling healthcare data.

Methods: Our analysis aims to elucidate the distinct strengths and weaknesses of each database in handling healthcare data. By contrasting the flexibility and user-friendliness of MongoDB with the extreme scalability of Cassandra and the high performance of Couchbase in distributed environments, this research empowers healthcare information technology professionals and database administrators to make informed decisions regarding NoSQL database selection.

Results: These findings contribute to the effective management of healthcare data, facilitating improved health outcomes.

Conclusions: This study analyzes performance demonstration in detail among MongoDB, Cassandra, and Couchbase, owing to the merits and demerits for healthcare applications. Real-time healthcare data processing is adequately assessed in terms of throughput, latency, scalability, and fault tolerance benchmarks for their appropriateness. The flexible features of MongoDB present multiple advantages, whereas, with respect to operations that require scalability at high performance, Cassandra is more usually chosen. This therefore should assist any healthcare IT professional in making the right decision for the selection of their NoSQL database when it comes to effective data management and enhanced outcomes for healthcare.