Student: Daniel Brunner     (Start: 2022)

Supervisor: a.Univ.-Prof. DI Dr. Wolfram Wöß
 

Abstract

Implementing and maintaining the backend of an application involves common duties like integrating databases, creating and maintaining APIs, ensuring security, upgrading performance, and writing server-side code. Consequently, a lot of experience and skills are required to fulfill these responsibilities. That's where Firebase and MongoDB Atlas come into play. Both application development platforms offer a toolkit to easily create the backend of an application. One of the most popular tools within this toolkit is an auto-scaling NoSQL database, which brings flexibility and outstanding performance to the table without the need for hosting and maintaining a server. Although Firebase and MongoDB share the commonality of providing a NoSQL database, there is divergence in how data is stored, structured, indexed, queried, and aggregated. These differences determine the capabilities and limitations of an application; therefore should be considered when choosing between Firebase and MongoDB Atlas. It can be quite difficult to find these differences or to compare the characteristics of one database provider with another, especially for someone new to the NoSQL database world. In this work, we will analyze the most significant discrepancies between Firebase's and MongoDB Atlas' data store and provide a criteria catalog that contributes to the decision-making between these two prominent application development platforms.