The Advantages of MongoDB Over Relational Database

Posted By : Anuj Kumar Sharma | 13-Apr-2020

MongoDB is a document database and a leading NoSQL database written in C++ that is extensively used in MEAN stack app development. In this blog, we will provide you a basic understanding of MongoDB concepts in SaaS development services for creating and deploing a scalable and performance-oriented database.



It is designed for Software Professionals who are willing to learn MongoDB Database in simple and easy steps. It gives concepts and after completing it will be at an intermediate level of expertise, from where we can take ourselves at a higher level of expertise.



We should have a basic understanding of database, text editor and execution of programs, etc. Because we are going to develop a database, so it will be good if you have an understanding of the basic concepts of Database (RDBMS).



The database is a physical container for collections. It gets its own set of files on the file system. A single MongoDB server typically has multiple databases.


Limitations of Relational Databases

1. In the relational database we need to define the structure and schema of data first and then only we can process the data.

2. Relational database systems provide consistency and integrity of data by enforcing (Atomicity, Consistency, Isolation, and Durability ). There are some scenarios where this is useful like the banking system. However, in most of the other cases, these properties are significant performance overhead and can make your database response very slow.

3. Most of the applications store their data in JSON format and RDBMS don’t provide you a better way of performing operations such as create, insert, update, delete, etc on this data. On the other hand, NoSQL stores its data in JSON format, which is compatible with most of today’s world applications.



A collection is a group of MongoDB documents. It is the equivalent of an RDBMS table. A collection exists within a single database. Collections do not enforce a schema. Documents within a collection can have different fields. Typically, all documents in a collection are of similar or related purposes.



A document is a set of key-value pairs. Documents have a dynamic schema. It means that documents in the same do not need to have the same set of rows, and common fields in a collection's documents may hold different types of data.


The following shows the RDBMS terminology with MongoDB.

Database Database
Table Collection
Tuple/Row Document
column Field
Table Join Embedded Documents
Primary Key Primary Key (Default key provided by itself)

Any relation has a typical design that shows the number of tables and the relationship between these tables. There is no concept of relationship.


Advantages of MongoDB Over RDBMS

  • Schemaless − MongoDB is a document database in which one collection holds different documents. The number of rows, material, and size of the document can differ from one document to another.

  • The structure of a single object is clear.

  • No complex joins.

  • Deep query-ability. It supports dynamic things on documents using a document-based query language that's near.

  • Tuning.

  • Ease of scale-out −It is easy to scale.

  • Application objects to DB object not needed.

  • Uses memory for storing the working set, enabling faster access.


Why Use MongoDB?

  • Document Storage − Data is stored in the form of JSON style documents.

  • Index on any attribute

  • Replication and high availability

  • Auto-Sharding

  • Rich queries

  • Fast in-place updates

  • Professional support by MongoDB


Where To Use MongoDB?

  • Big Data

  • Content Management and Delivery

  • Mobile and Social Infrastructure

  • User Data Management

  • Data Hub

About Author

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Anuj Kumar Sharma

He is having good knowledge in java, spring, and database and also have strengths like adaptability ,interactivity .

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