Although MySQL as an instance of relational database or SQL has been the most used database until now because of it being open source.
NoSQL has shown itself to be a formidable competitor with its forecast to be rising to $3.4 Billion by 2021.
Although the main difference between SQL and NoSQL database models would be the lack of structured query language in the latter, there are some viable differences between the two that we will review later in this article.
The two most notable SQL and NoSQL database model instances would respectively be MySQL and MongoDB although there are other relational [ SQL Server, Oracle ] and non-relational [ CouchDB, BigTable ] databases that are active in the data storage industry.
Furthermore we will compare the two architectures from different aspects:
NoSQL would be the superior in terms of language.
Because due to the restrictions that SQL databases have because of the fact that one has to use a predefined schema for your data before you can store it in your database but in NoSQL databases we do not have a predefined schema for data and each data can have its own unique structure.
Also you can add fields in your NoSQL database as you go but such thing in SQL databases is not possible.
My bet would be on NoSQL databases.
On SQL databases you can vertically scale your database meaning you can increase the load of a single server by increasing your CPU, RAM or SSD. But in NoSQL databases you can horizontally scale your database by handling more traffic.
Handling more traffic can be done by sharding or adding more servers to your NoSQL database.
Also let's take a look at the most famous NoSQL database which is MongoDB:
when we use this database on node.js frameworks, we use a common driver called mongoose, unlike SQL databases that use the incrementing mechanism to add counters to every row, MongoDB does not create objectId by itself, instead it calls it's driver(in this case mongoose) to generate unique objectIds for each document. This mechanism allows us to have several instances of mongodb and we do not have to talk to a central place to get a unique identifier Because the driver itself creates an almost unique identifier every time.
Note that mongoose is an abstraction over MongoDB driver, actually mongoose talks to the MongoDB driver to generate a new id.
By comparing the two methods we get to the conclusion that NoSQL databases can become larger therefore making them more scalable than SQL databases.
We cannot specify which structure between the two different databases is better because each structure could be useful in specific types of services and each carry conceptual differences.
SQL databases represent data in the form of tables which use columns and rows.
While NoSQL databases are document based and can store data in forms of graph, key-value pairs or wide-column stores.
Each of them solve specific scenarios and are very different from one another, in fact so much that what could be ideal for one, could not be for the other and vice versa. For example SQL allows related information to be produced while NoSQL is not able or very limited in doing so. Instead NoSQL allows you to posit larger amount of information compared to SQL. In SQL you can alter and manage the data and the relationships between them but in NoSQL data such things cannot happen.
Furthermore there will be examples regarding which areas which type of database can be used:
Any Project or enterprise would have their own specific requirements and preferences, so narrowing down the pros and cons of them to the point of choosing one of them would not be a solution at all.
For example applications with multi-row transactions such as accounting systems would work on SQL databases.
Where NoSQL databases such as MongoDB are used in enterprises with rapid growth or if you cannot define a specific schema for your database or if your data schema continuously changes which is the case for mobile applications, also for integration of BigData and for projects with easier scalability.
In the end, many may argue that NoSQL is a new technology that does not have its sets of standards unlike SQL databases such as MySQL. But it is always a necessity for developers to adapt and expose themselves to new technology after evaluating their pros and cons.