A Scalable Transaction Management Framework for Consistent Document-Oriented NoSQL Databases

TL;DR

This paper introduces a scalable transaction management framework for document-oriented NoSQL databases like MongoDB, improving consistency, reducing aborts, and enhancing performance through a four-stage process with conflict detection and adaptive locking.

Contribution

The study presents a novel four-stage transaction management framework that guarantees conflict serializability and improves performance in NoSQL databases, validated through extensive experiments.

Findings

Reduces transaction abort rates from 8.3% to 4.7%.

Eliminates observed deadlocks in experiments.

Achieves up to 18.4% throughput improvement under high concurrency.

Abstract

NoSQL databases are widely used in modern applications due to their scalability and schema flexibility, yet they often rely on eventual consistency models that limit reliable transaction processing. This study proposes a four-stage transaction management framework for document-oriented NoSQL databases, with MongoDB as the reference platform. The framework combines transaction lifecycle management, operation classification, pre-execution conflict detection, and an adaptive locking strategy with timeout-based deadlock prevention. Formal correctness analysis shows that the proposed approach guarantees conflict serializability under defined conditions. An experimental evaluation using the Yahoo Cloud Serving Benchmark (YCSB) workloads A, B, and F, with concurrency levels ranging from 1 to 100 clients, demonstrates a reduction in transaction abort rates from 8.3% to 4.7%, the elimination of observed deadlocks, and a 34.2% decrease in latency variance. Throughput improvements ranging from 6.3% to 18.4% are observed under high concurrency, particularly for read-modify-write workloads. Distributed experiments on clusters of up to 9 nodes confirm scalability, achieving 15.2% higher throughput and 53% lower abort rates than baseline systems. Comparisons with MongoDB's native transactions, CockroachDB, and TiDB indicate that the proposed framework strikes a good balance between consistency guarantees and performance overhead. Sensitivity analysis identifies optimal parameter settings, including a lock timeout of 100 ms, an initial backoff of 10 ms, and a maximum backoff of 500 ms. These results show that carefully designed consistency mechanisms can significantly improve data integrity in NoSQL systems without undermining scalability.