NexusDB: A Large-Scale Distributed Time-Series Database for Industrial Scenarios

Linlin Ding, Di Yuan Chzhen, Yuda Li, Zhiyong Zhang, Zhiran Xie, Mo Li

Abstract: With the development of Industrial Internet of Things (IIoT) and sensor technology, the speed and volume of data generation in industrial environments are rapidly increasing.In these settings, sensors continuously generate large volumes of data, traditional databases often fall short due to their focus on generality rather than continuous data flow. We propose NexusDB, a distributed time-series database tailored for such environments. NexusDB optimizes storage structures and query execution, offering streamlined architecture, high performance, minimal footprint, and robust distribution capabilities. Experimental results show that NexusDB significantly outperforms conventional time-series databases in both data insertion and querying, particularly in large-scale scenarios.