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Difference between RDBMS and MongoDB

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MongoDB is an open-source document-oriented database used for high volume data storage. It falls under the classification of a NoSQL database. NoSQL tool means that it doesn’t utilize the usual rows and columns. MongoDB uses BSON (document storage format) which is a binary style of JSON documents. 

Features of MongoDB:

  • Multiple Servers: It can run over multiple servers.
  • Schema-less Database: It is a schema-less database.
  • Indexing: Any field in the document can be indexed.
  • Rich Object Model: It supports a rich object model.
  • High scalability
  • Distributed database

What is RDBMS?

It stands for Relational Database Management System. It stores data in the form of related tables.
Features of RDBMS:

  • Gives a high level of information security.
  • It is quick and precise.
  • Provides facility primary key, to exceptionally distinguish the rows.
  • Schema-fix Database
  • Not scalable 

The trade-off between RDBMS and MongoDB:

Trade-off b/w RDBMS and MongoDB

Difference between RDBMS and MongoDB:

RDBMS MongoDB
It is a relational database. It is a non-relational and document-oriented database.
Not suitable for hierarchical data storage. Suitable for hierarchical data storage.
It is vertically scalable i.e increasing RAM. It is horizontally scalable i.e we can add more servers.
It has a predefined schema. It has a dynamic schema.
It is quite vulnerable to SQL injection. It is not affected by SQL injection.
It centers around ACID properties (Atomicity, Consistency, Isolation, and Durability). It centers around the CAP theorem (Consistency, Availability, and Partition tolerance).
It is row-based. It is document-based.
It is slower in comparison with MongoDB. It is almost 100 times faster than RDBMS.
Supports complex joins. No support for complex joins.
It is column-based. It is field-based.
It does not provide JavaScript client for querying. It provides a JavaScript client for querying.
It supports SQL query language only. It supports JSON query language along with SQL.

Last Updated : 22 Feb, 2023
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