This study aims to enhance data consistency in NoSQL databases, traditionally designed with BASE properties, as opposed to the strong consistency guaranteed by ACID principles in RDBMS. We introduce a comprehensive four-stage server-side model engineered explicitly for MongoDB. This model covers transaction management, bifurcation of read and write transactions, assessment of transaction readiness, and transaction execution via a specialized locking algorithm. Utilizing the Yahoo Cloud Services Benchmark (YCSB), particularly for update-heavy workloads (A, B, and F), our model exhibited significant improvements. Specifically, the average throughput, read, and update latencies improved to 2864.726 ms, 32806.275 ms, and 51845.629 ms, respectively, from the baseline metrics of 2914.110 ms, 26510.930 ms, and 32457.662 ms. These results demonstrate the efficacy of our proposed model in enhancing consistency not only in document-based NoSQL databases like MongoDB but also in other NoSQL database variants, including key-value, graph, and wide-column stores.

翻译：本研究旨在提升NoSQL数据库的数据一致性，该类数据库传统上基于BASE属性设计，与RDBMS中ACID原则保证的强一致性形成对比。我们提出了一种专门针对MongoDB的四阶段服务端模型，涵盖事务管理、读写事务分离、事务就绪性评估以及通过专用锁定算法执行事务。利用雅虎云服务基准测试（YCSB），特别是针对更新密集型工作负载（A、B和F类别），我们的模型显示出显著改进。具体而言，平均吞吐量、读取延迟和更新延迟分别从基准指标2914.110毫秒、26510.930毫秒和32457.662毫秒提升至2864.726毫秒、32806.275毫秒和51845.629毫秒。这些结果证明了我们提出的模型在增强一致性方面的有效性，不仅适用于MongoDB等基于文档的NoSQL数据库，也适用于其他NoSQL数据库变体，包括键值存储、图数据库和宽列存储。