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MongoDB vs MySQL | A Complete Comparison

By January 20, 2020 MongoDB
mongodb vs mysql

MySQL is the most inexpensive option for organizations around the world for those who require a relational database. As the assortment and volume of data have escalated lately, non-relational databases like MongoDB have advanced to meet the upcoming requirements of fluid data.

Comparison of these Quintessential Programmes on the basis of:


MySQL has been ageing since 1995 and has grown dramatically. Some of the organizations that use MySQL are Pinterest, Twitter, YouTube, Netflix, Spotify, US Navy, NASA, Walmart, and Paypal, amongst others whereas MongoDB was launched in 2009 and is put in used by numerous organizations like Klout, Citrix, Twitter, T-Mobile, Zendesk, Sony, Hootsuite, SurveyMonkey, MuleSoft, Foursquare, and InVision.

Database Structure

MySQL keeps its data in tables and uses the SQL, structured query language, to approach the data. It uses schemas to explain the database structure, compelling that all rows within a table consist of the same structure with values being represented by a specific data type whereas in the MongoDB the data is kept in JSON-like docs that can have assorted structures. To improve the speed of the query, MongoDB stores related data together, accessed using the MongoDB query language. It is schema-free, which allows you to curate docs without having to explain the structure of any doc first. These documents can be conveniently modified by adjoining or eliminating fields.

With the use of

The MongoDB data model, it abets you to display hierarchical relationships, data arrays, and complex structures in the database. Usually, MongoDB performance is escalated over MySQL as  MongoDB doesn’t use joins to connect data, which in turn improves performance.

database structure


MySQL and MongoDB use indexes that allow them to locate data quickly. With the use of MySQL, when an index is not defined, the database engine scans the entire table to find all of the relevant rows whereas in MongoDB, when an index is not found, every document within the collection is scanned to chose the documents that provide a match to the query.

Deployment of Databases 

MySQL is written in C and C++ and has binaries for the various systems like Microsoft Windows, OS X, Linux, AIX, BSDi, FreeBSD, HP-UX, IRIX, NetBSD, and many more whereas the MongoDB is written in C++, C, and JavaScript and has binaries for the systems like Linux, OS X, Solaris, and Windows.

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Availability of Replication / Clustering 

MySQL backs master-slave replication and master-master replication, the multisource replication permits you to simulate from numerous masters in parallel whereas the MongoDB backs built-in replication, sharding, and auto-elections. With the use of auto-elections, it permits you to set up a secondary database to spontaneously take over when the primary database fails.

database clustering Ownership

MySQL was established by the MySQL AB, a Finnish/Swedish company. Originally it was designed for personal use but later it evolved to be an enterprise-grade database whereas

MySQL is owned by the Oracle Corporation.

The Right  Database for your Business

Numerous factors to consider while choosing the right database are as follows:

MySQL: There are manifold cases for a relational database like MySQL. The type of application which needs multi-row transactions like an accounting system would be most suitable for a relational database. MongoDB is not a convenient replacement for legacy systems that are established for relational databases.

MongoDB: whereas there are numerous cases of use where MongoDB is the most suitable like some of which inculcate real-time analytics, content management, internet things, mobile, and various other apps, that are latest and grabble full advantage of what MongoDB offers. There is no clear schema definition in which makes MongoDB becomes an excellent choice. While adjoining new columns to a relational database like MySQL, it locks up the complete database and leads to performance issues. But MongoDB, due to it being schema-less, you can always add new fields without any hassle and without affecting existing rows.

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