MongoDB vs SQL Databases ~ GNIITHELP

It is a well known fact that SQL databases have ruled the world of data technologies and have been the primary source of data storage for over 4 decades. Generally the SQL databases are used, mainly for accessing relational databases.

Oracle and Microsoft SQL Server ruled the segment, but as the Web development market paced up, there came a shift towards usage of open source databases like MySQL, Postgres etc. But RDBMS was still the first choice.

Soon enough data started growing exponentially and scalability became a major issue, at that time NoSQL rolled in to save the day.

One of the cool facts about NoSQL databases is that they existed since 1960, but in the recent times they have gained more popularity especially for the scaling feature provided by the same.

The major difference between MongoDB and SQL Databases is the way they handle data. In SQL databases, data is stored in form of traditional 2 dimensional row-column structure while in MongoDB rich data document model is followed, which allows storage of any type of data.

Let us see some of the key differences between MongoDB and other SQL databases :

SQL Database	NoSQL Database (MongoDB)
Relational database	Non-relational database
Supports SQL query language	Supports JSON query language
Table based	Collection based and key-value pair
Row based	Document based
Column based	Field based
Support foreign key	No support for foreign key
Support for triggers	No Support for triggers
Contains schema which is predefined	Contains dynamic schema
Not fit for hierarchical data storage	Best fit for hierarchical data storage
Vertically scalable – increasing RAM	Horizontally scalable – add more servers
Emphasizes on ACID properties (Atomicity, Consistency, Isolation and Durability)	Emphasizes on CAP theorem (Consistency, Availability and Partition tolerance)

MongoDB Documents also align with the structure of objects in modern programming languages, as they are a form of JSON. This makes it easy for developers to map the data used in the application to its associated document in the database. While in SQL Database, creating a table with columns mapped to the attributes of an object in programming language, appears a little tedious.