In the current computing era, data are generating in exponential manner. These data are processed to extract information. This processing demands many query operations which in-turn requires the application of hashing for fast process of query operations. Cuckoo hashing is more efficient than conventional hashing techniques like open addressing, chaining and coalesced hashing. Because of simplicity and ease of use Cuckoo hashing has been used in real-world applications. Inherent problem associated with hashing is data collision and Cuckoo hashing also experiences the same. Cuckoo hashing uses endless loops,that results into high insertion latency and rehash operations. The idea behind Templing and Temple Search is to develop a robust hashing technique based on B-Tree that can efficiently handle the problem of data collisions without any changes in its underlying structure. In each bucket a separate B-Tree of same height is maintained to store the keys. Comprehensive analysis of experimental results demonstrate the potential of Templing and Temple Search. Templing and Temple Search addresses all challenges associated with Cuckoo hashing: intensive data migration, inefficient memory usages and high insertion latency.In future,Templing and Temple Search technique has great potential of its applications in the area of distributed hashing and in parallel hashing.