  Efficient management of RDF data plays an important role in successfully
understanding and fast querying data. Although the current approaches of
indexing in RDF Triples such as property tables and vertically partitioned
solved many issues; however, they still suffer from the performance in the
complex self-join queries and insert data in the same table. As an improvement
in this paper, we propose an alternative solution to facilitate flexibility and
efficiency in that queries and try to reach to the optimal solution to decrease
the self-joins as much as possible, this solution based on the idea of
"Recursive Mapping of Twin Tables". Our main goal of Recursive Mapping of Twin
Tables (RMTT) approach is divided the main RDF Triple into two tables which
have the same structure of RDF Triple and insert the RDF data recursively. Our
experimental results compared the performance of join queries in vertically
partitioned approach and the RMTT approach using very large RDF data, like DBLP
and DBpedia datasets. Our experimental results with a number of complex
submitted queries shows that our approach is highly scalable compared with
RDF-3X approach and RMTT reduces the number of self-joins especially in complex
queries 3-4 times than RDF-3X approach
