Empirical Analysis of Performance Parameters for Consistency in Distributed Databases - Krishan, Kewal; Gupta, Gaurav; Bhathal, Gurjit Singh (International Journal of Intelligent Systems and Applications in Engineering, 2023)
The contemporary era presents a significant obstacle in terms of data storage and retrieval. Horizontal scaling of data across various standard hardware configurations can yield benefits such as improved availability, enhanced performance, and increased fault tolerance. This objective can be attained through the process of replication. Nonetheless, a significant obstacle encountered in this endeavour is the lack of uniformity. This indicates that a single datum is associated with varying values across multiple locations simultaneously. Numerous theoretical frameworks have been posited in the field of literature to tackle this particular predicament. Therefore, this paper undertakes an analysis of multiple consistency models and subsequently compares them based on their respective contributing factors. This paper considers various factors such as Linearizability, Serializability, Strict Serializability, Sequential Consistency, Casual consistency, ACID and BASE in order to compare different models. Consequently, by virtue of this comparison, diverse consistency models may be chosen for the system to enhance its performance and availability.