Welcome to a tutorial on MongoDB. Here you learn why and when to go for MongoDB.
You should know that MongoDB is not a replacement for any traditional RDMS databases. However, MongoDB structures/stores the data in the form of BSON (Binary representation of JSON) which happens to be a self-explaining and human-readable data format as well as a way it provides the scaling feature to the application to be developed.
MongoDB employs more data insertion rate over the safety concerns of doing inserts in a transaction. Therefore, the write consistency is low. In a situation where there is a need for a huge load of data to be written, without considering the loss of data, hence, the preferred Database to use is MongoDB.
In this case, if the recovery process of data needs to be faster, safe, and automatic, then we can use MongoDB.
In MySQL, if a database or a few tables become corrupt, one can repair them individually by simply deleting/updating the data. But, in MongoDB, all you need to do is to repair on a database level, interestingly, there is a command to do this automatically, although it reads all the data and re-writes it to a new set of files. Therefore, if we have a huge database, it might take some time, and during that time your Database will be locked. But, it is preferable to lose your dataset completely.
MongoDB is the best option when data grows infinitely and proper load balancing of the same is required. This is because it supports faster replica setting options and its built-in Sharding feature.
Now, if a developer does not want to normalize its data and insists on not using any JOINS, then he should go for MongoDB. Take for instance, if there are 2 collections of students and addresses (that is a case where a student can have more than one address). Hence, in a typical RDBMS, to fetch the addresses associated with a student from the address table, JOIN is used. However, in MongoDB, the address data can be embedded as a document in the student collection itself. Therefore, without making use of any JOIN all the required details of the student and address can be fetched with one just a query.
db.address.insert([
{
_id: 'addr1',
name: 'USA'
},
{
_id: 'addr2',
name: 'Australia'
}
]);
db.student.insert([
{
_id: 's1',
name: 'Alex',
address: ['addr1']
},
{
_id: 's2',
name: 'Justin',
address: ['addr1','addr2']
},
]);It is commonly known that if a table in any RDBMS is altered (like adding a new column or row), there is a high possibility that the entire database might get locked which in turn results in big performance degradation. But with MongoDB which is schema-less, adding new fields will not result in any problem.
In a situation where the data to be stored does not need to be a relational one, then MongoDB should be selected.