A study of performance comparison of databases for HALF data archiving system

Abstract

Abstract The Hefei Advanced Light Facility (HALF) is a 2.2 GeV fourth-generation synchrotron radiation light source. The HALF control system is a distributed control system based on Experimental Physics and Industrial Control System (EPICS). As the essential part of the HALF control system, the Historical Data Archiving System (HDAS) is responsible to store operational data for the entire facility including the accelerator and beamlines, and provides the functions for data query and analysis. According to the estimation based on the HALF scale, approximately 25,000 EPICS PVs will be stored in HDAS, and these accumulated massive data require a dedicated database for persistent storage and management. Under the EPICS PV data scenario of HALF, a fair database test platform is designed and built to test the read-write performance of databases commonly used in the particle accelerator field. The tested objects include EPICS Archiver Appliance and the five databases MongoDB, HBase, InfluxDB, TimescaleDB, and Cassandra. Additionally, research on the five databases software ecosystem is conducted for the development and extension of HDAS. The test results indicate that TimescaleDB has the fastest read performance, and 1.4×10^6 items of data can be read per second. TimescaleDB also has superior write performance. 1.2 × 105 items of data can be written per second, which can fully meet the writing requirements of HDAS. Regarding the software ecosystem, TimescaleDB is compatible with a larger number of data visualization software and big data processing frameworks. Therefore, TimescaleDB is more suitable as the HDAS database. In the future, a TimescaleDB distributed cluster will be designed and deployed, and an HDAS prototype system will be developed based on this cluster.