Dalbergia odorifera T. Chen is one of China's endangered species. It is also an endemic species that mainly distributes in Hainan, Guangdong, Fujian, etc. Dalbergia odorifera has great values in medicine, economics and ecology, and its medicinal properties are specified in the Chinese Pharmacopoeia. But the resource was reduced and the productivity was declined due to years of deforestation. Developing mixed forests of Dalbergia odorifera has been becoming a major trend of Chengmai farm in Hainan Province, because mixed forests can not only adjust the temperature and relative humidity of woodland, but also improve soil fertility. Soil can provide nutrition for aboveground vegetations, as well as soil microorganisms. Soil bacteria, as one of the key members of soil microorganisms, plays an important role in promoting organic matter decomposition, accelerating mineral nutrition cycle, maintaining and improving soil fertility. People can understand the soil status better by analyzing the relationship between soil bacterial community and soil characteristics, and finally develop a method to improve the Dalbergia odorifera plantation. However, only about 1% bacteria could be assayed by traditional methods. High-throughput sequencing is a new method that can get the classification information of soil bacteria more conveniently and accurately, and avoid the limitations of traditional methods. This method has been widely used in studying soil microorganisms. We investigated soil bacteria diversity in four different mixed forests of Dalbergia odorifera plantation, i.e. Dalbergia odorifera mixed with Dalbergia oliveri, Pterocarpus macarocarpus, Santalum album L. and Homalium hainanense Gagnep., respectively, in Chengmai County, Hainan Province in China. A high-throughput sequencing technique was used to analyze the relationship and differences among these four plots to find a way that could improve soil fertility of Dalbergia odorifera plantation. After analyses, the results showed that soil physical-chemical characteristics and soil enzyme activities were different in the four mixed forest, i.e. the Dalbergia odorifera and Santalum album L. mixed forests with higher moisture content, organic matter, total N, available K and Ureas; Dalbergia odorifera and Pterocarpus macarocarpus mixed forests with higher pH, available P and polyphenol oxidase. The results of high-throughput sequencing showed that soil bacterial abundances of these four plantations were: Dalbergia odorifera × Santalum album L. > Dalbergia odorifera × Pterocarpus macarocarpus > Dalbergia odorifera × Dalbergia oliveri > Dalbergia odorifera × Homalium hainanense Gagnep., and the soil bacteria diversity of these four mixed models were: Dalbergia odorifera × Pterocarpus macarocarpus > Dalbergia odorifera × Dalbergia oliveri > Dalbergia odorifera × Santalum album L. > Dalbergia odorifera × Homalium hainanense Gagnep.. The dominant bacteria taxa in the four mixed forests were Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi and Firmicutes. The results of redundancy analysis and correlation analysis showed that pH, Ureas, polyphenol oxidase and organic matter were the main factors that had significant effect on the structure and diversity of soil bacterial community in this four mixed forests. Our analysis of bacteria 16S rRNA-based dataset showed differences in soil bacterial community structure among four mixed forests of Dalbergia odorifera. But further research is also needed to get more information in soil microorganisms.