In recent years, with the vigorous development of computer science and wireless sensor network, how to address big trajectory data is becoming a concerned issue increasingly. Because of massive trajectory data, there is an increasing focus on storage and search of big trajectory data. In view of this, based on the document type non relational database MongoDB, we propose a spatio-temporal index of road network which is based on quad-tree. For the 1915 taxis in Taiyuan, the 500,000 pieces of trajectory data are searched. With different data and different number of concurrency, we compare the efficiency of spatio-temporal index with that of MongoDB composite spatio-temporal index. Experimental results show that our method performs well when data volume is larger than 100000. It can adapt to spatio-temporal queries with different number of concurrency, proving that the method is feasible and efficient.