Plugging and Playing with Variety of Data using Multi-Model Database and Polyglot Persistence
Shelly Sachdeva, Jignisa Vasava · 2024
This paper explores handling variety of data (structured, semi-structured, and unstructured). It discusses various data models and compares them based on speed, storage, and use case scenarios. To leverage the management of diverse types of data, the current research focuses on two main approaches: multi-model database and polyglot persistence. Utilizing diverse data optimizes storage by employing a multi-model database that accommodates various data models within a single database. On the other hand, polyglot persistence stores data across multiple databases, which a mediator handles. Interoperability among healthcare entities is particularly challenging due to the diverse nature of healthcare. The study stands out by assessing scalability and performance analysis using a multi-model database and polyglot persistence on a healthcare dataset. This paper stores the healthcare dataset in a multi-model database (ArangoDB) and performs various queries to demonstrate its functionality. It has been observed during implementation that polyglot persistence manages diverse types of data by leveraging SQLlite and MongoDB within a single web application backend, facilitating flexible data management tailored to specific data models. Plugging and playing with a variety of data offers a flexible solution to manage variety of data effectively in modern healthcare settings.