EDUCBA

EDUCBA

MENUMENU
  • Free Tutorials
  • Free Courses
  • Certification Courses
  • 360+ Courses All in One Bundle
  • Login
Home Data Science Data Science Tutorials Head to Head Differences Tutorial MySQL vs MongoDB
Secondary Sidebar
Head to Head Differences Tutorial
  • Differences Tutorial
    • Scikit Learn vs TensorFlow
    • Azure Functions vs Logic Apps
    • Azure Data Factory vs Databricks
    • SHA1 vs MD5
    • Azure SQL Database vs Managed Instance
    • Azure SQL Database vs SQL Server
    • PostgreSQL vs MySQL
    • PostgreSQL vs MySQL Benchmark
    • ArangoDB vs MongoDB
    • Cloud Computing vs Big Data Analytics
    • T-SQL vs SQL
    • PostgreSQL vs MariaDB
    • Spark vs Impala
    • Datadog vs Splunk
    • Domo vs Tableau
    • Data Scientist vs Data Engineer vs Statistician
    • Big Data Vs Machine Learning
    • Predictive Analytics vs Business Intelligence
    • AI vs Machine Learning vs Deep Learning
    • Business Intelligence vs Data Warehouse
    • Apache Kafka vs Flume
    • Data Science vs Machine Learning
    • Business Analytics Vs Predictive Analytics
    • Data mining vs Web mining
    • Data Science Vs Data Mining
    • Data Science Vs Business Analytics
    • Analyst vs Associate
    • Apache Hive vs Apache Spark SQL
    • Apache Nifi vs Apache Spark
    • Apache Spark vs Apache Flink
    • Apache Storm vs Kafka
    • Artificial Intelligence vs Business Intelligence
    • Artificial Intelligence vs Human Intelligence
    • Al vs ML vs Deep Learning
    • SQL vs SQLite
    • Assembly Language vs Machine Language
    • AWS vs AZURE
    • AWS vs Azure vs Google Cloud
    • Big Data vs Data Mining
    • Big Data vs Data Science
    • Big Data vs Data Warehouse
    • Blu-Ray vs DVD
    • Business Intelligence vs Big Data
    • Business Intelligence vs Business Analytics
    • Business Intelligence vs Data analytics
    • Business Intelligence VS Data Mining
    • Business Intelligence vs Machine Learning
    • Business Process Re-Engineering vs CI
    • Cassandra vs Elasticsearch
    • Cassandra vs Redis
    • Cloud Computing Public vs Private
    • Cloud Computing vs Fog Computing
    • Cloud Computing vs Grid Computing
    • Cloud Computing vs Hadoop
    • Computer Network vs Data Communication
    • Computer Science vs Data Science
    • Computer Scientist vs Data Scientist
    • Customer Analytics vs Web Analytics
    • Data Analyst vs Data Scientist
    • Data Analytics vs Business Analytics
    • Data Analytics vs Data Analysis
    • Data Analytics Vs Predictive Analytics
    • Data Lake vs Data Warehouse
    • Data Mining Vs Data Visualization
    • Data mining vs Machine learning
    • Data Mining Vs Statistics
    • Data Mining vs Text Mining
    • Data Science vs Artificial Intelligence
    • Data science vs Business intelligence
    • Data Science Vs Data Engineering
    • Data Science vs Data Visualization
    • Data Science vs Software Engineering
    • Data Scientist vs Big Data
    • Data Scientist vs Business Analyst
    • Data Scientist vs Data Engineer
    • Data Scientist vs Data Mining
    • Data Scientist vs Machine Learning
    • Data Scientist vs Software Engineer
    • Data visualisation vs Data analytics
    • Data vs Information
    • Data Warehouse vs Data Mart
    • Data Warehouse vs Database
    • Data Warehouse vs Hadoop
    • Data Warehousing VS Data Mining
    • DBMS vs RDBMS
    • Deep Learning vs Machine learning
    • Digital Analytics vs Digital Marketing
    • Digital Ocean vs AWS
    • DOS vs Windows
    • ETL vs ELT
    • Small Data Vs Big Data
    • Apache Hadoop vs Apache Storm
    • Hadoop vs HBase
    • Between Data Science vs Web Development
    • Hadoop vs MapReduce
    • Hadoop Vs SQL
    • Google Analytics vs Mixpanel
    • Google Analytics Vs Piwik
    • Google Cloud vs AWS
    • Hadoop vs Apache Spark
    • Hadoop vs Cassandra
    • Hadoop vs Elasticsearch
    • Hadoop vs Hive
    • Hadoop vs MongoDB
    • HADOOP vs RDBMS
    • Hadoop vs Spark
    • Hadoop vs Splunk
    • Hadoop vs SQL Performance
    • Hadoop vs Teradata
    • HBase vs HDFS
    • Hive VS HUE
    • Hive vs Impala
    • JDBC vs ODBC
    • Kafka vs Kinesis
    • Kafka vs Spark
    • Cloud Computing vs Data Analytics
    • Data Mining Vs Data Analysis
    • Data Science vs Statistics
    • Big Data Vs Predictive Analytics
    • MapReduce vs Yarn
    • Hadoop vs Redshift
    • Looker vs Tableau
    • Machine Learning vs Artificial Intelligence
    • Machine Learning vs Neural Network
    • Machine Learning vs Predictive Analytics
    • Machine Learning vs Predictive Modelling
    • Machine Learning vs Statistics
    • MariaDB vs MySQL
    • Mathematica vs Matlab
    • Matlab vs Octave
    • MATLAB vs R
    • MongoDB vs Cassandra
    • MongoDB vs DynamoDB
    • MongoDB vs HBase
    • MongoDB vs Oracle
    • MongoDB vs Postgres
    • MongoDB vs PostgreSQL
    • MongoDB vs SQL
    • MongoDB vs SQL server
    • MS SQL vs MYSQL
    • MySQL vs MongoDB
    • MySQL vs MySQLi
    • MySQL vs NoSQL
    • MySQL vs SQL Server
    • MySQL vs SQLite
    • Neural Networks vs Deep Learning
    • PIG vs MapReduce
    • Pig vs Spark
    • PL SQL vs SQL
    • Power BI Dashboard vs Report
    • Power BI vs Excel
    • Power BI vs QlikView
    • Power BI vs SSRS
    • Power BI vs Tableau
    • Power BI vs Tableau vs Qlik
    • PowerShell vs Bash
    • PowerShell vs CMD
    • PowerShell vs Command Prompt
    • PowerShell vs Python
    • Predictive Analysis vs Forecasting
    • Predictive Analytics vs Data Mining
    • Predictive Analytics vs Data Science
    • Predictive Analytics vs Descriptive Analytics
    • Predictive Analytics vs Statistics
    • Predictive Modeling vs Predictive Analytics
    • Private Cloud vs Public Cloud
    • Regression vs ANOVA
    • Regression vs Classification
    • ROLAP vs MOLAP
    • ROLAP vs MOLAP vs HOLAP
    • Spark SQL vs Presto
    • Splunk vs Elastic Search
    • Splunk vs Nagios
    • Splunk vs Spark
    • Splunk vs Tableau
    • Spring Cloud vs Spring Boot
    • Spring vs Hibernate
    • Spring vs Spring Boot
    • Spring vs Struts
    • SQL Server vs PostgreSQL
    • Sqoop vs Flume
    • Statistics vs Machine learning
    • Supervised Learning vs Deep Learning
    • Supervised Learning vs Reinforcement Learning
    • Supervised Learning vs Unsupervised Learning
    • Tableau vs Domo
    • Tableau vs Microstrategy
    • Tableau vs Power BI vs QlikView
    • Tableau vs QlikView
    • Tableau vs Spotfire
    • Talend Vs Informatica PowerCenter
    • Talend vs Mulesoft
    • Talend vs Pentaho
    • Talend vs SSIS
    • TensorFlow vs Caffe
    • Tensorflow vs Pytorch
    • TensorFlow vs Spark
    • TeraData vs Oracle
    • Text Mining vs Natural Language Processing
    • Text Mining vs Text Analytics
    • Cloud Computing vs Virtualization
    • Unit Test vs Integration Test?
    • Universal analytics vs Google Analytics
    • Visual Analytics vs Tableau
    • R vs Python
    • R vs SPSS
    • Star Schema vs Snowflake Schema
    • DDL vs DML
    • R vs R Squared
    • ActiveMQ vs Kafka
    • TDM vs FDM
    • Linear Regression vs Logistic Regression
    • Slf4j vs Log4j
    • Redis vs Kafka
    • Travis vs Jenkins
    • Fact Table vs Dimension Table
    • OLTP vs OLAP
    • Openstack vs Virtualization
    • Cluster v/s Factor analysis
    • Informatica vs Datastage
    • CCBA vs CBAP
    • SPSS vs EXCEL
    • Excel vs Tableau
    • Cassandra vs MySQL
    • RabbitMQ vs Kafka
    • SAAS vs Cloud
    • RabbitMQ vs Redis
    • AMQP vs MQTT
    • Forward Chaining vs Backward Chaining
    • Google Data Studio vs Tableau
    • ActiveMQ vs RabbitMQ
    • Cloud vs Data Center
    • Cores vs Threads
    • Inner Join vs Outer Join
    • ZeroMQ vs Kafka
    • Mxnet vs TensorFlow
    • Redis vs Memcached
    • RDBMS vs NoSQL
    • AWS Direct Connect vs VPN
    • Cassandra vs Couchbase
    • Elegoo vs Arduino
    • Redis vs MongoDB
    • Chef vs Puppet
    • GSM vs GPRS
    • Keras vs TensorFlow vs PyTorch
    • Cloudflare vs CloudFront
    • Bitmap vs Vector
    • Left Join vs Right Join
    • IaaS vs PaaS
    • Blue Prism vs UiPath
    • GNSS vs GPS
    • Cloudflare vs Akamai
    • GCP vs AWS vs Azure
    • Arduino Mega vs Uno
    • Qualitative vs Quantitative Data
    • Arduino Micro vs Nano
    • PIC vs Arduino
    • PRTG vs Solarwinds
    • PostgreSQL vs SQLite
    • Metabase vs Tableau
    • Arduino Leonardo vs Uno
    • Arduino Due vs Mega
    • ETL Vs Database Testing
    • DBMS vs File System
    • CouchDB vs MongoDB
    • Arduino Nano vs Mini
    • IaaS vs PaaS vs SaaS
    • On-premise vs off-premise
    • Couchbase vs CouchDB
    • Tableau Dimension vs Measure
    • Cognos vs Tableau
    • Data vs Metadata
    • RethinkDB vs MongoDB
    • Cloudera vs Snowflake
    • HBase vs Cassandra
    • Business Analytics vs Business Intelligence
    • R Programming vs Python
    • MongoDB vs Hadoop
    • MySQL vs Oracle
    • OData vs GraphQL
    • Soft Computing vs Hard Computing
    • Binary Tree vs Binary Search Tree
    • Datadog vs CloudWatch
    • B tree vs Binary tree
    • Cloudera vs Hortonworks
    • DevSecOps vs DevOps
    • PostgreSQL Varchar vs Text
    • PostgreSQL Database vs schema
    • MapReduce vs spark
    • Hypervisor vs Docker
    • SciLab vs Octave
    • DocumentDB vs DynamoDB
    • PostgreSQL union vs union all
    • OrientDB vs Neo4j
    • Data visualization vs Business Intelligence
    • QlikView vs Qlik Sense
    • Neo4j vs MongoDB
    • Postgres Schema vs Database
    • Mxnet vs Pytorch
    • Naive Bayes vs Logistic Regression
    • Random Forest vs Decision Tree
    • Random Forest vs XGBoost
    • DynamoDB vs Cassandra
    • Looker vs Power BI
    • PostgreSQL vs RedShift
    • Presto vs Hive
    • Random forest vs Gradient boosting
    • Gradient boosting vs AdaBoost
    • Amazon rds vs Redshift
    • Bigquery vs Bigtable
    • Data Architect vs Data Engineer
    • DataSet vs DataTable
    • dataset vs dataframe
    • Dataset vs Database
    • New Relic vs Splunk
    • Data Architect and Management Designer
    • Data Engineer vs Data Analyst
    • Grafana vs Tableau
    • MySQL text vs Varchar
    • Relational Database vs Flat File
    • Datadog vs Prometheus
    • Neo4j vs Neptune
    • Data Mining vs Data warehousing
    • DocumentDB vs MongoDB
    • PostScript vs PCL
    • QRadar vs Splunk
    • Qlik Sense vs Tableau
    • DigitalOcean vs Google Cloud
    • PostgreSQL vs Elasticsearch
    • Redshift vs blueshift
    • Gitlab vs Azure DevOps

Related Courses

Online Data Science Course

Online Tableau Training

Azure Training Course

Hadoop Certification Course

Data Visualization Courses

All in One Data Science Course

MySQL vs MongoDB

By Priya PedamkarPriya Pedamkar

MySQL vs MongoDB

Differences Between MySQL vs MongoDB

MySQL is a database system used in Web Development, MySQL is developed, marketed and supported by MySQL  AB, which is a Swedish company. MySQL is very fast, easy-to-use. It uses a standard form of the well-known SQL data language. It supports large databases, up to 50 million rows or more in a table. MongoDB is a NoSQL Database, it is a cross-platform, document-oriented database that provides, high availability, high performance, and easy scalability. MongoDB works on the concept of collection and document.

MySQL

  • You have nothing to pay to use it because MySQL is released under an open-source license. It works on many operating systems and with many languages including C++, JAVA, PHP, PERL, C, etc. The open-source GPL license allows programmers to modify the MySQL software to fit their own specific environments.
  • The default file size limit for a table is 4GB, We can increase this (if our operating system can handle it) to a theoretical limit of 8 million terabytes (TB). It works very quickly and works well even with large datasets. It handles a large subset of the functionality of the most expensive and powerful database packages.
  • It compiles on many platforms. It is named after co-founder Monty Widenius’s daughter: My. Data stored in MySQL tables, Tables are collections of related data. Tables have row and columns to store data, Tables are related by different keys like primary keys, Foreign keys, etc.

MongoDB

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

MySql Stores date in from Tables Example given below

ID FirstName LastName Age Email
312 John roy 44 john@gmail.com

MongoDB stores data in form Documents Example given below.

{

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

_id: ObjectId(7df38ad8902c)

All in One Data Science Bundle(360+ Courses, 50+ projects)
Python TutorialMachine LearningAWSArtificial Intelligence
TableauR ProgrammingPowerBIDeep Learning
Price
View Courses
360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (86,171 ratings)

title: ‘MongoDB Test’,

description: ‘MongoDB is no sql DB’,

by: ‘by me’,

url: ‘http://www.xyz.com’,

MySQL vs MongoDB

tags: [‘mongodb’, ‘database’, ‘NoSQL’],

likes: 100,

comments: [

{

user:’user1′,

message: ‘thinking to ask question’,

dateCreated: new Date(2011,1,21,2,15),

like: 0

},

{

user:’user2′,

message: ‘how we are going to use please help me’,

dateCreated: new Date(2011,1,27,7,45),

like: 5

}

]

}

In the above documents   _id is a 12 bytes hexadecimal number which assures the uniqueness of every document. We can provide _id while inserting the document. If we don’t provide then MongoDB provides a unique id for every document. These 12 bytes first 4 bytes for the current timestamp, next 3 bytes for machine id, next 2 bytes for process id of MongoDB server, and remaining 3 bytes are simple incremental values.

Head to Head Comparison Between MYSQL vs MongoDB (Infographics)

Below are the top 6 differences between MYSQL and MongoDB:

MySQL-vs-MongoDB-info

Key Differences Between MYSQL and MongoDB

Let us discuss some of the major difference between MYSQL and MongoDB:

In MySQL: if an index is not defined, the database engine must scan the entire table to find all relevant rows.

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.

Selecting records from the customer table:

In MySQL: SELECT * FROM customer In MongoDB: db.customer.find()

Inserting records into the customer table:

In MySQL: INSERT INTO customer (cust_id, branch, status) VALUES (‘appl01’, ‘main’, ‘A’)

In MongoDB: db.customer.insert({ cust_id: ‘appl01’, branch: ‘main’, status: ‘A’ })

Updating records in the customer table:

In MySQL:  UPDATE customer SET branch = ‘main’ WHERE custage > 2

In MongoDB:  db.customer.update( { custage: { $gt: 2 } }, { $set: { branch: ‘main’ } }, { multi: true } )

MySQL is written in C and C++ and has binaries for the following systems: Microsoft Windows, OS X, HP-UX ,Linux, AIX, BSDi, FreeBSD, , IRIX, NetBSD, and more.

MongoDB was written in C++, C, and JavaScript and has binaries for the following systems: Linux, OS X, Solaris, and Windows.

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.

MongoDB: 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 and MongoDB Comparison Table

Below is the comparison table between MYSQL and MongoDB.

Basis Of Comparison  MYSQL MongoDB
Definition MySQL is a relational database system that is open source, no need to pay money to use it. MongoDB is a NoSQL database, it stores data in form of a document that contains a document id that is always unique.
Structure to store MySQL stores its data in tables and uses the structured query language (SQL) to access the data. 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.  MongoDB, data is stored in JSON-like documents that can have varied structures. To improve query speed, MongoDB can store related data together, which is accessed using the MongoDB query language. MongoDB is schema-free, allowing you to create documents without having to define the structure of the document first.
 

Benefits

It has fixed schemas, use SQL to find the data It does not require schemas, It json based. used unstructured queries.
Real Time Usage Legacy system those required data stored in the tabular form like banking application. Content management, Real-time analytics, Internet of things, mobile.
Industry Pinterest, Twitter, YouTube, Netflix, Spotify, US Navy, NASA, Walmart, and Paypal Citrix, Twitter, T-Mobile, Zendesk, Sony, Hootsuite, SurveyMonkey, MuleSoft, Foursquare, and InVision
Generation MySQL has been maturing since 1995. MongoDB was released in 2009.

Conclusion

Both MySQL vs MongoDB have their own advantages and disadvantages .which one has to use totally depends on our project requirement. If we are dealing with the banking system which maintains users’ transactions or legacy system in these cases MySQL selection will be the best choice while in the case of an Internet of things, Mobile, Content Management, analytics MongoDB will be the best choice.

Recommended Articles

This has been a guide to the top difference between MYSQL vs MongoDB. Here we also discuss the MYSQL vs MongoDB head-to-head comparison key differences along with infographics and a comparison table. You may also have a look at the following MYSQL vs MongoDB articles to learn more –

  1. MySQL vs MSSQL
  2. MongoDB vs Oracle
  3. SQL Server vs MySQL
  4. DBMS and RDBMS
Popular Course in this category
MongoDB Training Program (4 Courses, 2 Projects)
  4 Online Courses |  2 Hands-on Projects |  22+ Hours |  Verifiable Certificate of Completion
4.5
Price

View Course

Related Courses

Data Scientist Training (85 Courses, 67+ Projects)4.9
Tableau Training (8 Courses, 8+ Projects)4.8
Azure Training (6 Courses, 5 Projects, 4 Quizzes)4.7
Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes)4.7
Data Visualization Training (15 Courses, 5+ Projects)4.7
All in One Data Science Bundle (360+ Courses, 50+ projects)4.7
1 Shares
Share
Tweet
Share
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • Corporate Training
  • Certificate from Top Institutions
  • Contact Us
  • Verifiable Certificate
  • Reviews
  • Terms and Conditions
  • Privacy Policy
  •  
Apps
  • iPhone & iPad
  • Android
Resources
  • Free Courses
  • Database Management
  • Machine Learning
  • All Tutorials
Certification Courses
  • All Courses
  • Data Science Course - All in One Bundle
  • Machine Learning Course
  • Hadoop Certification Training
  • Cloud Computing Training Course
  • R Programming Course
  • AWS Training Course
  • SAS Training Course

ISO 10004:2018 & ISO 9001:2015 Certified

© 2022 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA
Free Software Development Course

C# Programming, Conditional Constructs, Loops, Arrays, OOPS Concept

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA Login

Forgot Password?

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA
Free Software Development Course

Web development, programming languages, Software testing & others

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy

Loading . . .
Quiz
Question:

Answer:

Quiz Result
Total QuestionsCorrect AnswersWrong AnswersPercentage

Explore 1000+ varieties of Mock tests View more