Decades of research and experiences on organizing the large databases and contemporary world’s resilient interests in gigantic data, information transferred various indexing techniques to a new level. From all-encompassing experiments, the PFB+-tree has exhibited its excellent prospective for big data in-memory management system. The PFB+-tree does quick indexing structure by utilizing range searches, point searches and multi-level key ranges are quickened by prior pruning of searches to get distrait data. The depth-first or breath-first searching methods are used for range searches. One consortium of various searches can be set upwards with only single pass on indexing structure to reduce the time complexity. The LSB+-tree can speed up queries directed to the most accessed ranges of indices. Extended experiments are presented to show and high efficiency, particularly for testing its adaptability and performance for big data storage management.