Backstory:
I'm building an e-commerce web app (online store) Now I got to the point of choosing a database system and an appropriate design. I got stuck with developing a design for product attributes
I've been considering of choosing NoSQL (MongoDB) or SQL database systems
I need you advice and help
The problem:
When you choose a product type (e.g. table) it should show you the corresponding filters for such a type (e.g. height, material etc.). When you choose another type, say "car", it provides you with the car specific filter attributes (e.g. fuel, engine volume)
For example, here on one popular online store if you choose a data storage type you get a filter fo this type attributes, such as hard drive size or connection type
Question
What approach is the best for such a problem? I described some below, but maybe you have your own thoughts in regard to it
MongoDB
Possible solution:
You can implement such product attrs structure pretty easy.
You can create one collection with a field attrs for each product and put there whatever you want, like they suggest here (field "details"):
https://docs.mongodb.com/ecosystem/use-cases/product-catalog/#non-relational-data-model
The structure will be
Problem:
With such a solution you don't have product types at all so you can't filter the products out by their types. Each product contains it's own arbitrary structure in attrs field and don't follow any pattern
Ir maybe I can somehow go with this approach?
SQL
There are solutions like single table where all the products store in one table and you end up with as many fields as an attribute number of all the products taken together.
Or for every product type you create a new table
But I won't consider these ones. One is very bulky and another one isn't much flexible and requires a dynamic scheme design
Possible solution
There is one pretty flexible solution called EAV https://en.wikipedia.org/wiki/Entity%E2%80%93attribute%E2%80%93value_model
Our schema would be:
Such a design may be done on MongoDB system, but I'm not sure it's been made for such a normalised structure
Problem
The schema is going to get really huge and really hard to query and grasp


