Study of Consistency and Performance Trade-Off in Cassandra

Abstract

Cassandra is a distributed database with great scalability and performance that can manage massive amounts of data that is not structured. The experiments performed as a part of this paper analyses the Cassandra database by investigating the trade-off between data consistency andperformance. The primary objective is to track the performance for different consistency settings. The setup includes a replicated cluster deployed using VMWare. The paper shows how difference consistency settings affect Cassandra's performance under varying workloads. The results measure values for latency and throughput. Based on the results, regression formula for consistency setting is identified such that delays are minimized, performance is maximized and strong data consistency is guaranteed. One of our primary results is that by coordinating consistency settings for both read and write requests, it is possible to minimize Cassandra delays while still ensuring high data consistency.