A Surfing Concurrence Transaction Model for Key-Value NoSQL Databases

Abstract

As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, many scholars have tried different techniques. Unfortunately, there is a lack of research on Redis's transaction in the existing literatures. This paper proposes a transaction model for key-value NoSQL databases including Redis to make possible allowing users to access data in the ACID (Atomicity, Consistency, Isolation and Durability) way, and this model is vividly called the surfing concurrence transaction model. The architecture, important features and implementation principle are described in detail. The key algorithms also were given in the form of pseudo program code, and the performance also was evaluated. With the proposed model, the transactions of Key-Value NoSQL databases can be performed in a lock free and MVCC (Multi-Version Concurrency Control) free manner. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology.

Evaluation of Database Management Systems and Techniques Applied in Distributed Systems

“…As more and more big data-related application systems are developed, Database systems based on NoSQL are becoming increasingly popular but there are various drawbacks to NoSQL databases, like as SQL is not supported, which is an industry standard, and there are no reports or any extra capabilities, with the proposed model, the transactions of Key-Value NoSQL databases may be used in a lock-free and Multi-Version Concurrency Control free manner Li and Gu (2018). In distributed system, it is investigated that the improvement of employing cachebased query optimization to reduce response time is suitable option because it saves huge computational cost and time, especially introducing cache at each site instead of implementation of one network-based cache however, it is observed that currently cache is implemented only in homogeneous distributed databases Rana et al (2018).…”

“…Transaction client, transaction manager, transaction sorter, transaction dispatcher, transaction executor, and actors are the six functional components. The waiting queue, the waiting read queue, the waiting write queue, the waiting execution queue, the executing queue, and the finished execution queue are the six queues Li and Gu (2018).…”