K-mer Mapping, an internal process for De Novo NGS genome fragments assembly methods, constitutes a computational challenge due to its high main memory consumption. We present a study of index-based methods to deal with this problem, considering a RDBMS environment. We propose an ad-hoc I/O cost model and analyze the performance of hash and B-tree versions for index structures. Furthermore, we present a novel approach for an index based on hashing that takes into account the notion of minimum substrings. An actual RDBMS implementation for experiments with a sugarcane dataset shows that one can obtain considerable performance gains while reducing main memory requirements.