Summary: Time-series data are the key to industrial development. The aggregation operation of the data is an important step in practice. However, traditional relational databases fail to support vast amounts of time-series data. The NoSQL databases are inefficient and require time-consuming calculation to aggregate of time-series data. This paper presents an efficient index mechanism that supports time-series data aggregation by combining a synopsis table and a segment tree. A query algorithm based on this mechanism introduces the synopsis table into the NoSQL database and builds a segment tree from the synopsis table for archiving that is lb\(n\) the size of the original query set. This query algorithm can directly locate a series of index data to be queried without the recursive operations in traditional trees and effectively reduces I/O overhead. This study shows the efficiency of this index mechanism by comparisons with general index mechanisms.