With the advent of high time resolution observational instruments using CMOS sensors, the amount of observational data has increased dramatically in recent years. We have developed a new data archive system for the TriCCS data of the Seimei Telescope, one of such instruments. In the development of the new system, we have tried to solve the technical challenges that were identified with the SMOKA/Tomo-e Gozen data archive system. This paper reports the results of the development and discusses future challenges and a data server concept to deal with them.

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In this paper, we report on experiments conducted to speed up searches in the optical-infrared astronomical observation data archive system and their results. High-speed or wide-field imaging instruments like Tomo-e Gozen and Hyper Suprime-Cam generate a huge amount of observational data. Such recent surge in data volume leads to a slowdown in data search speed in the data archive system. We conduct experiments to speed up searches using the database of SMOKA/Tomo-e Gozen system, which archives Tomo-e Gozen data, and its SQL queries. Concretely, we explore optimal table partitioning and parallel query settings, SSD-based table file placement impact, and PostGIS R-tree spatial indexing effects.The results reveal that increasing the number of table partitions and utilizing SSDs reduce cache-invalidated execution time and using PostGIS shortens cache-enabled spatial query execution time. The maximum reduce rates of each experiment are about 83 %, 98 %, and 91 %, respectively. This paper elaborates on the details of these experiments and discusses the suitable database settings for the data archive systems having a huge amount of observation data.

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