Preprocessing texts of huge size to answer substring queries is not trivial whenever considering realistic models. We approach this problem by offering an efficient implementation of the String B-Tree data structure, which aims to solve the sub-string search problem under the dynamic operations. We achieve optimal space usage for the Patricia Tries by representing them via multiarray encoding and our approach for the String B-Tree uses less space than any other external memory full-text index available. The tree representation is well suited for entropy compression and the String B-Tree is efficiently constructed regarding CPU processing and I/O operations. During that construction process we reuse the SA and the LCP arrays, which can be generated by other efficient algorithms.