Cnos-Connector: Enabling Seamless Connection with CnosDB to Facilitate Large-Scale Time-Series Data Management and Analytics

Time-series data is being increasingly generated in real-world applications. To process the massive data with high performance, we have introduced CnosDB, a distributed database tailored for time series to achieve high writing speed and storage efficiency. To allow the users to seamlessly integrate the superior time series database into their applications, in this paper, we propose Cnos-connector, a generic, easy-to-use, and flexible tool that enables the users to simply interact with CnosDB using the wrapped Python functions. Cnos-connector adapts for Python Database API Specification v2.0 (PEP 249), a popular interface framework that has been used by many Python libraries (e.g. Pandas), so that they can be used in conjuction with each other to improve the usability. We plan to demonstrate how the users integrate CnosDB into their applications in various scenarios using Cnos-connector.