A Configurable Data Comparison Tool for Digital System Evolution
Gang Wu, Ruiguang Lv, Dechao Feng, Zhaolong Li · 2025
With the proliferation of digital services, maintaining system stability during functional iterations and architectural refactoring has become a critical challenge for online platforms. Current industry practices rely on ad-hoc implementations of dual-write mechanisms and data comparison logic embedded within business code, which inherently lack standardization and scalability. This paper proposes a configurable data comparison tool that provides a common solution through four key innovations: (1) rule-based configuration obviating manual coding, (2) a robust comparison engine guaranteeing consistent accuracy across heterogeneous scenarios, (3) real-time tunability via centralized configuration management, and (4) multi-channel discrepancy alerts (SMS/IM). Empirical results demonstrate measurable improvements across key metrics: (1) increased R&D productivity, (2) superior quality of data comparison functionalities, (3) reduced deployment frequency, and (4) optimized discrepancy alerting throughput.