Today, the massive advancement in computer science has led everyone to make excessive attempts to achieve the best performance even by tiny margins. This motivates them to create new data structures, perfect for their purpose but usually not beneficial in other conditions. The result is that the field is overran with different kinds of data structures, all good for one purpose but untested for many others, therefore comparing them isn’t always beneficial or sensible if the conditions are variable. We aim to unite these structures into a mechanism that will select and apply the best structure depending on the application and workload that emerges, by profiling each one under many scenarios. This way, the programmer can be completely ignorant to the underlying structure and the execution will always handle the traffic efficiently, even when the traffic changes patterns systematically.