  Efficient PV research which includes a prolonged data monitoring from
multiple experiments with different characteristics, requires a scalable
supporting system to handle all of the collected information. This paper
presents the development of a relational database for hosting all the necessary
information for data modeling, comparative analysis and O\&M systems.
Ramer-Douglas-Peucker algorithm and Timescaledb compression are used to
decrease the size of the time-series data and increase the performance of the
queries. A decision-making algorithm is presented for selecting the optimal
inputs to the Ramer-Douglas-Peucker algorithm to ensure the maximum disk space
savings while not losing any of the necessary information. Furthermore,
alternative ways of implementing the same database are provided.
