Document categorization, as a technique to improve the retrieval of useful documents, has been extensively investigated. One important issue in a large-scale meta-search engine is to select text databases that are likely to contain useful documents for a given query. We believe that database categorization can be a potentially effective technique for good database selection, especially in the Internet environment, where short queries are usually submitted. In this paper, we propose and evaluate several database categorization algorithms. This study indicates that, while some document categorization algorithms could be adopted for database categorization, algorithms that take into consideration the special characteristics of databases may be more effective. Preliminary experimental results are provided to compare the proposed database categorization algorithms.