MongoDB : Is this relational database more effective than MySQL?
What is the difference between relational and non-relational databases?
The relational database is the main type of database mainly used by developers. To better understand it, you must consider data as many different objects linked with each other’s. One object could be attached to many others or just coupled with one. There are several kinds of relation between these objects:
- The one to many relation 1-n,
- The many to many n-n,
- The one to one 1-1.
Non-relational databases also link objects between them. However, its ability to analyse and manage objects is way more efficient. There are logically preferred when it comes to Big Data operations. Nevertheless, they are a bit complex to use: It is important to present the different types of NoSQL Database:
- Functioning on a key-value principle : One data is considered as the key and it is linked to another data considered as the value.
- The column-oriented databases : SQL relational databases stock data in columns. The non-relational ones also do that, but the NoSQL version provides column with a changing number of lines.
- Documents oriented databases : MongoDB belongs to that category. Objects are saved under XMl or Json format.
- Graphs bases : Tailored to treat complex relation.
Non-relational databases are mainly used for Big Data because they allow the management of numerous data. So, why to use MongoDB? What are the features? This is what we are going to see.
Special features of MongoDB
MongoDB is an opensource non-relational NoSQL database developed by 10gen in 2007? As we have already seen, MongoDB is very documents oriented. In 10 years, MongoDB has succeeded to conquer a lot of users. Nowadays, it is the most used NoSQL database especially for Nod.Js platforms.
- Several types of server’s connexion:Mongo Shell client, MongoChef, RoboMongo or Mongoclient could be considered to use MongoDB.
- Compatibility of MongoDB : Linux, Windows, Mac.
The uses of MongoDB
Non-relational databases are mostly used to treat a large amount of unstructured data. MongoDB is often chosen to store and exploit diverse files not exactly following the normal process.
MongoDB has the advantage to be able to horizontally scale on several servers without any dysfunction. It is perfect for large websites. In the other hand, the data are divided on different servers, it ensures a full availability of the application.
MongoDB or MySQL: What are the similitudes?
- Collections : Most of databases store objects in tables. This is not the case for MySQL or MongoDB, they store data into collections.
- BSON format : Used by both, to replace lines and fields in files but also requests’ columns.
- Value and names of fields : It is the common composition shared by MongoDB and MySQL.
- Key/value : It defines a MongoDB document just as a document used in MySQL
MongoDB or MySQL: Main differences?
- The files’ management : In a MySQL table, the different lines have the same composition. On the other, the amount and types of values are always the same. So, when a MySQL should be edited, it is necessary to rethink it entirely. MongoDB has not the same issue, every file has its own structure. A non-relational database’s table could be edited or filled whenever the users needs to. Another point of difference, in a non-relational database, the key could be in several files, this is not the case for MySQL for instance.
- Data’s extraction : Data processing done by MongoDB is made through its own language and it uses libraries. The tool is able to communicate with the client considering it is able to use its language. This is not possible with a MySQL database (a relational one)
MongoDB or MySQL: Which one you should go for?
There is not one right answer here. Indeed, MongoDB and MySQL are very different and has very different purpose. They could be easily combined to provide a fully tailored solution to the user. On the other hand, for the same goal, these two types of database could not be compared considering the amount of difference in terms of structure and usages.