CnosDB: A Flexible Distributed Time-Series Database for Large-Scale Data

Abstract

With the development of the Internet of Things, the time series data generated by monitors, analyzers, and detection instruments in the industry has surged. The management of very large-scale time series data faces great challenges. However, the current distributed time series database is still poor in terms of data storage efficiency and data writing speed. In order to achieve the fast writing and high efficient storage of billions or even tens of billions of data points, we propose a cloud native distributed time series database, CnosDB. Our system integrates various data compression algorithms to achieve high compression rate in each data type. And we propose a three-layer storage policy to achieve fast writing under the premise of ensuring rapid time-based batch operations. In this paper, introduce the architecture and key techniques of CnosDB, and describe three key demo scenarios of our system.