1. A method for processing time series data from multiple sensors, wherein the multiple sensors are divided into multiple sensor groups and each time series data comprises a time stamp and a value associated with the timestamp, the method comprising: a data receiving step of receiving time series data from each sensor of the multiple sensors; a data grouping step of assigning the time series data received from each sensor to a sensor group to which the sensor belongs among the multiple sensor groups; a first storing step of storing time series data in a first database of a first memory, such that multiple time series data assigned to the same sensor group in the multiple sensor groups are stored in at least one database record of the first database; a data re-organizing step of obtaining the time series data of each sensor among the multiple sensors from the first database; and a second storing step of storing time series data as per the values in a second database of a second memory, such that the multiple time series data from the same sensor are stored in at least one database record of the second database, the second storing step storing said time series data as per the values comprising: calculating a probability distribution function PDF for values from each sensor; dividing the values from each sensor into multiple value ranges based on the calculated PDF; and storing time series data based on the divided value ranges, such that one database record comprises time series data corresponding to values within the same value range.