The past few years have seen a huge spike in the number of websites and apps using NoSQL databases. With MongoDB topping the charts everywhere. It is indeed fascinating how the modern web has drifted away from traditional SQL based databases. MongoDB and other NoSQL databases have a new approach in storing and retrieving data. So let us have a look at some of the key factors in which MongoDB differs from MySQL.
With a traditional SQL database like MySQL, we need to have a fixed data structure. It is expected that we know what different types of data is going to be recorded. We have to beforehand create the Database, required tables, columns and even specify data-type for each column. This isn’t the case with MongoDB. With MongoDB, developers are allowed to be a little laid back. Forget tables and data-types, you don’t even need to create a database. MongoDB automatically does most of the initial heavy lifting for you.
MongoDB works on the idea of collections. These collections are like tables but without any fixed number of columns. So each document(a document is the MySQL equivalent for a row/record) in a collection can have a different structure. They may or may not have the same number of fields(a field is the MySQL equivalent of column). So one can say that MySQL has a fixed schema and MongoDB has a flexible Schema.
Searching for Data
Searching for data in your database can be a very easy task in MySQL. We have support for things like joins that can help combine data from multiple tables. But this again requires that you very well know your data model. Concepts like Foreign keys allow you to create relations between different datasets. This helps maintain data integrity.
MongoDB has a very different approach in searching for data thanks to its flexible schema. Searching for data is very limited as joins are not available in Mongo. You are expected to put whatever data is needed in just one document since nesting is allowed. This is one of the things that really bothers new developers working on mongo. Overall I would say that SQL is very rich when it comes to searching for data and MongoDB is pretty limited.
Constraints and Data Integrity
Since you have to predefine data models with SQL, there is nothing to worry about integrity. The database will not accept any type of data that doesn’t follow the standards. Constraints like a foreign key, primary key, and unique indexes take a lot of hassle away from the developer.
On the other hand, though MongoDB lags behind. It does offer several types of integrity based indexes including the unique index, but there isn’t a constraint on the datatype. And its totally understood since the fields aren’t fixed themselves. It is hence, very commonly seen that ORM’s(Object Relationship Mapper) are very frequently used with MongoDB. They are used for performing integrity checks on server side code. To sum it up, SQL is very strict and rich with data integrity whereas MongoDB is not.
Every successful app needs to be scaled up at some point. When the number of users grows, multiple servers are needed. This is where the factor of being able to scale pops up. Traditionally SQL databases were built to scale vertically, i.e scaling by increasing the hardware on the same machine. This would cause trouble if that server were to collapse for some reason.
On the other hand, MongoDB was built to scale horizontally. You could set up multiple nodes that would automatically replicate themselves with no single point of failure. Though MySQL has seen great improvement with MySQL Cluster, it is still not comparable to MongoDB. When it comes to scaling out, MongoDB fares far better than MySQL.
MongoDB and MySQL have 2 completely different database systems. One believes in keeping things atomic while the other believes in grouping them up. MySQL has always been and still stays the default choice for many when it comes to databases. However, we see that changing and people are opting for MongoDB.
MongoDB caters to the needs of modern apps better than MySQL But MySQL has a far better edge in handling relational data. At the end of the day, it is just a matter of what you want to do. Both the options are pretty solid and are being used by some of the biggest companies on the internet. I hope I’ve made the major differences clear between MySQL and MongoDB. If you still have a doubt, drop it in the comments section and I’ll be there for you.
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