Providing Scalability to Data Layer Using a Novel Polyglot Persistence Approach
Subhash Nadkarni, Akshen Kadakia, Kriti Shrivastava · 2018
Efficiency of a system is totally dependent on how fast data is accessed from the data layer. It is not necessary that the data layer has to be a single type store. With the advancement in computer engineering nowadays we have many flavors of data store, each paradigm having its unique advantages and drawbacks. The challenge in reaping benefits from these diverse technologies is to integrate these various data stores together to have a hybrid data layer and map appropriate data to relevant data store such that scalability is not affected. In this paper, we have proposed a novel data mapping approach based on polyglot persistence. We have demonstrated this hybridization concept for e-commerce domain to achieve better performance than its traditional standalone counterparts.