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Damián Gil

Advisor at Empresa En Crecimiento
Advisor at Empresa En Crecimiento·
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MongoDBMongoDB

I am in your spot, exactly. A few months ago, I had decided to use Postgres because since its version 9 it showed a lot of progress for being a high-availability database. However, frankly, I didn't want to model statically all data, since I have several distinct schemas (like for different product types) and I wanted some flexibility to add or remove as I saw fit. One of the main challenges with analyzing a NoSQL database being familiar in the SQL ways, is that it's easy to look for "analogies" for what makes SQL useful, like relationship enforcing, transactions and the cascading effect on deletes, updates and inserts, and that limit your vision a lot when analyzing a tool like Mongo, especially in a micro-services pattern. Now-a-days, I really found my solution in Mongo. Not just because of it being NoSQL, but because all of the support I find in the NodeJS community through packages and utilities that make it dead easy to use it for several use-cases. Whatever Postgres offers, Mongo does it a little easier and better, like text search and geo-queries. What you need to see is to model your data in a way that makes sense with Mongo. For instance, I've got a User service that has all auth related information of a user. But then, I have the same user in the Profile service, with the same id, but totally different fields. You have two de facto ways to connect data, by reference and embedding, which in Ecommerce, both have big uses. Like using references to relate a User to a Profile, and an embed to relate a Product to an Order. There's even a third, albeit a little more "manual" implementation here, the graph relationship in which you can model data, in which you can easily model event-driven documents, like a Purchase that goes from "a customer" to "a store", which you can later use for much easier and deep analytics than with the classical SQL stance. MariaDB has it readily available, and also has many improvements over MySQL and Postgres, especially for NoSQL features and scalability. Sadly it is just seen as a MySQL clone, but it offers more than that (although its documentation could be improved). Using Mongo in a micro-service environment is even better because your models can be smaller, meaning less burden on relationships, although you do compensate with a bit of duplication, but a well-designed schema will have minimal impact on that. Whatever tool might do the job, but I want to cheer on the newer generation. Hope it helps.

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