Reason 1: Misconceptions about MongoDB

MongoDB was marketed as a general-purpose highly scalable database, but it was not. While it’s true that MongoDB is highly scalable for certain use cases where the data is structured in a particular way, it’s not the best choice for every project. Some developers chose to use MongoDB because they heard that it was a faster, more scalable alternative to traditional SQL databases. However, this is not always the case. It’s important to understand the strengths and weaknesses of both SQL and NoSQL databases before deciding which one to use.

Reason 2: Inexperienced programmers

At the initial stages of a company, when a non-technical founder is driving the project, the initial project tend to be written by inexperienced programmers like interns or volunteers who can make the wrong choice. Inexperienced developers may not fully understand the implications of choosing a NoSQL database like MongoDB over a SQL database. They may not be aware of the performance issues that can arise when using a NoSQL database like a relational database.

Reason 3: Bias towards relational way of developing applications

Frameworks with packages like Rails + Mongoid and Node + Mongoose.js make it easy to integrate MongoDB into a project, but the main frameworks themselves have a bias towards building applications in a relational way as they rely on ORM (Object-relational mapping) for their data models. This bias can make it difficult for developers to take advantage of MongoDB’s NoSQL capabilities where you need to increase redundant data to stay performant. This can lead to performance issues when the dataset grows and start using joins to make the application work. Joins are highly inefficient in MongoDB.

Reason 4: Building on Top of an Existing Stack

As other developers build on top of the existing stack, it can exacerbate the problem. Once a project is started with MongoDB, it can be challenging to migrate to a different database without breaking existing code. As more developers work on the project, the codebase can become more and more entangled with MongoDB-specific code, making it even harder to migrate to a different database.

In conclusion, while MongoDB and other NoSQL databases are often marketed as more scalable alternatives to SQL databases, it’s important to understand that this scalability comes with trade-offs. NoSQL databases like MongoDB are designed to be schema-less, which makes them more flexible than SQL databases and inflexible in other ways. If a NoSQL database like MongoDB is used like a relational database in an application, it will not scale well. Ironically, scalability is often the main reason why people end up migrating away from Mongo to SQL, despite the push towards NoSQL databases being more scalable.

When choosing between SQL and NoSQL databases, it’s important to understand the strengths and weaknesses of each. Developers should also be aware of the potential performance issues that can arise when using a NoSQL database like a relational database. If scalability becomes an issue, migrating to a SQL database may be the best solution. However, it’s important to consider the potential challenges of migrating away from MongoDB once you’ve already started using it.

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