We have implemented the Smith and Waterman dynamic programming algorithm on the massively parallel MP1104 computer from MasPar and compared its ability to detect remote protein sequence homologies with that of other commonly used database search algorithms. Dynamic programming algorithms are normally too computer intensive to permit full databases search, however on the MP1104 a search of the Swiss-Prot database takes about 15 s. This nearly interactive speed of database searching permits one to optimize the parameters for each query. Most of the common database search methods (FASTA, FASTDB and BLAST) gain their speed by using approximations such as word matching or eliminating gaps from the alignments which prevents them from detecting remote homologies. By using queries from protein super families containing a large number of family members of diverse similarities, we have measured the ability of each of these algorithms to detect the remotest members of each super family. Using these super families, we have found that the algorithms, in order of decreasing sensitivity are BLAZE, FASTDB, FASTA and BLAST. Hence the massively parallel computers allow one to have maximal sensitivity and search speed simultaneously.