As there is a huge surge in the on-demand application market, businesses are looking to build feature-rich applications across platforms. Database management of such high functioning application is complex and tedious. With large coding structures and programming to incorporate all the changes and updates that will be integrated at various stages of app development.
There are two major DBMS in the market, which are open-sourced, free and most popular too. They are MongoDB and MySQL. MongoDB is developed by MongoDB inc. and MySQL is developed by Oracle. It is important to know them very well when it comes to choosing the right DBMS.
MongoDB: An Introduction
MongoDB was conceptualised in 2007 and launched in 2010 by MongoDB inc. It employs key-value pairs known as a document store. These document stores are created and maintained in BSON files, which are a modified version of JSON files. The use of modified JSON files allows the exchange of data between web applications and human-readable servers. There is no schema implementation, providing flexibility in the design of code structure.
It allows hierarchal relationships representation and changes in records onboard. With NoSQL or un-structured query language, MongoDB provides facilities of auto-sharding and embedding and mirroring.
MySQL: An Introduction
Originally, designed as MySQL AB by Oracle, this DBMS is a relational database management system or RDBMS. MySQL employs the storage of data in vertical columns and horizontal rows. It uses structured query language for data access and transfers through commands like SELECT, INSERT, UPDATE, DELETE.
Related information is stored in different tables reducing the possibility of data duplication. MySQL uses pr-defined schema designs, which can’t be changed.
MongoDB has a single most important edge over MySQL and that is its ability to handle large unstructured data. It is magically faster because it allows users to query in a different manner that is more sensitive to workload. It also allows more RAM and CPU slice for queries to run faster.
In the MongoDB database, one can partition and shard the database with the In-built sharding feature. You can specify a shard key and sharding is enabled, which partitions the data evenly according to the shard key. MongoDB also possess an auto replica feature which allows replicating of data and imparting them primary and secondary role according to the scenarios at any point, in the entire process, It also improves the flow rate of operations by providing built-in special functions that help in finding specific data from specific locations with accuracy to boost up the overall process.
MongoDB uses security features, which include authentication, auditing, and authorization and you can also use Transport Layer Security (TLS) and Secure Sockets Layer (SSL) for encryption purposes. This ensures that it is only accessible and readable by the intended client.
While MySQL authenticates a user and facilitates it with user privileges on a particular database such as CREATE, SELECT, INSERT, UPDATE, and in doing so, it fails to explain why a given user is denied specific access.
When to use MongoDB?
MongoDB can be used when you need to build a cloud-based application for multi-platforms. When there is a need for instant and fast data recovery, totally automated. When you need to reduce your schema migration cost without a database administrator.
When to use MySQL?
MySQL can be used if your database is not scaled yet and want a low maintenance setup. If you want high performance on a limited budget and with a fixed schema. There will be no major changes in the near future and there would be high transactions. The most important parameter is data security as MySQL is a totally secure database.
Scaling is done in two ways, vertically and horizontally. Vertical scaling includes adding more powerful RAM and CPU processing power to the same machine. While horizontal scaling is to add more machines to your pool adding RAM power and CPU processing power by unilateral distribution.
MySQL databases are vertically scalable, which means that you can increase the load on a single server by increasing things like CPU, RAM or SSD. MongoDB databases are horizontally scalable. You can handle more traffic by sharding, or adding more servers in your MongoDB database.