Wednesday, October 27, 2021

    MongoDB vs MySQL

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    database is a collection of information that is organized so that it can be easily accessed, managed and updated. Depending upon the usage requirements, there are following types of databases available in the market like commercial database, NoSQL database, Operational database, Relational database, etc. MySQL is an open-source relational database management system. MongoDB is a cross-platform document-oriented database program and classified as a NoSQL database program. We will discuss MongoDB vs MySQL.



    MongoDB was released in 2009. MySQL has been maturing since 1995 and has grown a large following. MySQL is currently owned by the Oracle Corporation.
    MongoDB, Inc Supplies Ongoing Development. Oracle Corporation  Supplies Ongoing Development
    MongoDB was written in C++, C, and JavaScript and has binaries for the following systems: Linux, OS X, Solaris, and Windows. MySQL is written in C and C++ and has binaries for the following systems: Microsoft Windows, OS X, Linux, AIX, BSDi, FreeBSD, HP-UX, IRIX, NetBSD, and more.
    MongoDB used by many organizations including Klout, Citrix, Twitter, T-Mobile, Zendesk, Sony, Hootsuite, SurveyMonkey, MuleSoft, Foursquare, and InVision. MySQL used by Pinterest, Twitter, YouTube, Netflix, Spotify, US Navy, NASA, Walmart, and Paypal.
    In MongoDB, data is stored in JSON-like documents that can have varied structures. MySQL stores its data in tables.
    To improve query speed, MongoDB can store related data together, which is accessed using the MongoDB query language. MySQL uses the structured query language (SQL) to access the data.
    MongoDB is schema-free, allowing you to create documents without having to define the structure of the document first. These documents can be easily changed by adding or deleting fields. MySQL uses schemas to define the database structure, requiring that all rows within a table have the same structure with values being represented by a specific data type.
    In MongoDB, if an index is not found, every document within a collection must be scanned to select the documents that provide a match to the query statement. With MySQL, if an index is not defined, the database engine must scan the entire table to find all relevant rows.
    Queries Example:

    ({ stu_id: '101', branch: 'A' })
    Queries Example:

    SELECT * FROM student
    INSERT INTO student 
    (stu_id, branch) VALUES ('l01','A')
    MongoDB supports built-in replication, sharding, and auto-elections. Using auto-elections, you can set up a secondary database to automatically take over if the primary database fails. Sharding allows for horizontal scaling, which is difficult to implement in MySQL. MySQL supports master-slave replication and master-master replication (as of MySQL 5.7.6 and later). Multisource replication allows you to replicate from several masters in parallel.


    • Provides high performance
    • Auto-sharding
    • Run over multiple servers
    • Supports Master-Slave replication
    • Data is stored in the form of JSON style documents
    • index any field in a document
    • It has an automatic load balancing configuration because of data placed in shards


    • Scalable
    • Easy to use
    • High Security
    • Supports Novell Cluster Services
    • Fast
    • Runs on many operating systems

    Pros of MongoDB

    • Support ad-hoc query
    • High-Speed Database
    • Schema-less database
    • Horizontally scalable database
    • Performance is very high

    Pros of MySQL

    • supports large databases, up to 50 million rows or more in a table
    • open-source
    • Implement a variety of user interfaces

    Cons of MongoDB

    • Doesn’t support joins
    • Data Size is High
    • Nesting of documents is limited
    • Increase unnecessary usage of memory

    Cons of MySQL

    • No built-in support for XML or OLAP
    • Support is available for the free version
    • Take a lot of time and effort to create incremental backups


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