Cryptomeria japonica (sugi) and Chamaecyparis obtusa (hinoki) are major Japanese timber species whose plantation area accounts for 44% and 25%, respectively, of the plantation forests in Japan. Physiology, anatomy and ecology of the species have been intensively studied for this half century, which now form a huge stock of information. These data, however, were scattered in diverse sources, including papers, bulletins of research institutes, reports of other kinds and books, and were presented in non-standardized, diverse styles in each source. This paper provides a database (SugiHinoki DB) that compiles 177 plant traits of sugi and hinoki from 364 primary sources published since 1950. The compiled traits include physiological, morphological, anatomical and biochemical features that are recognized as relevant to life-history strategies, vegetation modeling and global change responses. Collected data had been obtained under different environmental conditions, for plants with different age, and for organs with different age or different position, which provide information of within species variation for a given trait. Each data entry is accompanied by detailed ancillary information describing the site of measurement, stand of measurement and detailed measurement conditions, which help users to account for data variations as a consequence of phenotypic plasticity and genetic variations and to filter data. To provide data in a consistent format, the data and the ancillary information were standardized, and units were converted. After data compilation, outliers were detected by calculating interquartile rage (IQR) for each trait per each species. In Aug 2019, SugiHinokiDB contains 24683 data entries (16410 for sugi, 8273 for hinoki). As sugi and hinoki are major plantation species in Japan, the data were mostly come from study sites in Japan (from Hokkaido in the north to Yakushima island in Kyushu, to the south), but were also from arboretums or plantation forests in Taiwan, Korea and China. Data were largely obtained for plants in plantation forests but also plants in natural forests and under experimental conditions. The improved availability of trait data offered by SugiHinokiDB provide new research opportunities such as intensive parameterization of vegetation models for more accurate prediction of climate change impacts.