Enhancement of Database Access Performance by Improving Data Consistency in a Non-relational Database System (NoSQL)

This study aims to improve data consistency in NoSQL databases, which traditionally follow BASE properties instead of the strong consistency guaranteed by ACID principles in RDBMS. We have developed a four-stage server-side model specifically for MongoDB to achieve this. Our model addresses transaction management, separation of read and write transactions, assessment of transaction readiness, and transaction execution using a specialized locking algorithm. We tested our model using the Yahoo Cloud Services Benchmark (YCSB), particularly for update-heavy workloads (A, B, and F). Our model showed significant improvements, with the average throughput, read, and update latencies improving to 2864.726 ms, 32806.275 ms, and 51845.629 ms, respectively, as compared to the baseline metrics of 2914.110 ms, 26510.930 ms, and 32457.662 ms. These results demonstrate that our proposed model effectively enhances consistency in document-based NoSQL databases like MongoDB and other NoSQL database variants, including key-value, graph, and wide-column stores.