What are some Challenges Involved in MongoDB while Data Modeling?

It was 2011-12, since then I have been working on MongoDB, that time SQL was used widely since RDBMS was a preferred database for enterprises. Also, in countries like India and developing nations, the usage of internet was pacing up, so the need for arousal of non-RDBMS was not heeded. But still many begin adopting MongoDB or NoSQL for enterprises.

Let’s peek a bit inside:

MongoDB is a type of a NoSQL Database only, in the JSON format. Thus, data modelling is easy on it. As a developer, you will be just dumping in data that is mimicking your application’s object or in some cases the ORM in frameworks like Django and so on.

Earlier, I experienced where a senior architect came to me and asked me, “So, how do you do database design and ER diagrams on MongoDB?” Well, my reply was if you have already decided to choose MongoDB then because of the following reasons:

The data is either semi-structured or unstructured: it means how will data model look is not sure.

This is the main reason behind preferring a NoSQL database like MongoDB.

Well, there are other reasons and case studies on scaling where people would choose MongoDB over the traditional RDBMS.

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