Recently, technology forecasting is becoming increasingly important as the diversity of technology intensifies and technological advances progress rapidly. In response, several attempts have been made to forecast future technologies by utilizing patent data. Patent data, however, have limitations on forecasting future technologies because they only include information about the past and existing technologies. To overcome these limitations, the use of futuristic data is suggested in this study. Futuristic data are composed of detailed predictions of the technology that various experts, such as managers of leading global companies and futurologists, explained based on their own perspectives. Since futuristic data are outcomes of collecting these predictions, they are helpful in developing foresights, and can be a suitable source for predicting future technologies. The primary purpose of this study is to compare patent data and futuristic data by identifying the distinction between the two. Unlike patent data, which are focused on technological details, futuristic data would contain expert information about social influence or predictable phenomena. In order to capture the difference of contents in two sources, this study utilizes text mining and clustering and draws a comparison between two sets of keyword clusters extracted from each database. In addition, compared to patent data, which deals with developed technologies, futuristic data can contain various technological applications that are not realized yet. The relationships between technologies and their applications in database, therefore, need to be investigated to compare the variety of technological applications in two sources. To this end, we construct the network of clusters and keywords.