In this paper, a novel method for Chinese Natural Language Interface of Database (NLIDB) based on Chinese paraphrase was proposed to solve the problems of traditional methods based on syntactic parsing which cannot obtain high accuracy and need a lot of manual label training corpus. First, key entities of user statements in databases were extracted, and candidate tree sets and their tree expressions were generated. Then most relevant semantic expressions were filtered by paraphrase classifier which was obtained from the Internet Q&A training corpus. Finally, candidate trees were translated into Structured Query Language (SQL). F1 score was respectively 83.4% and 90% on data sets of Chinese America Geography (GeoQueries880) and Questions about Restaurants (RestQueries250) by using the proposed method, better than syntactic based method. The experimental results demonstrate that the NLIDB based on paraphrase can handle the semantic gaps between users and databases better.