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 MSSQL
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
    • Data Science vs Artificial Intelligence
    • 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

MySQL vs MSSQL

By Priya PedamkarPriya Pedamkar

MySQL vs MSSQL

Difference Between MySQL and MSSQL

MySQL vs MSSQL is relational database management systems (RDBMS). RDBMS is a piece of software that stores information in a tabular format i.e. rows and columns. Each row and column is called a record and field respectively. Structured Query Language (SQL) is the means to interact with database systems for the creation, updating, and deletion of data.

MySQL

MySQL was initially released by the Sweden based firm MySQL AB in 1995 as an open-source RDBMS (Relational Database Management System). Later, Oracle Corporation acquired the MySQL AB. Currently, the open-source variant of the MySQL is available under the terms of GNU GPL (General Public License) and the proprietary version is governed by the terms of Oracle Inc., of course, with additional functionalities. MySQL is one of the components of the open-source LAMP (Linux, Apache, MySQL, PHP/Python/Perl) web development technology stack. Owing to its high performance, MySQL is widely used by large technology giants in varieties of applications including TYPO3, MODx, Joomla, WordPress, Drupal, Google, Facebook, Twitter, Flickr, and YouTube, among others.

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

MSSQL

MSSQL Server is a proprietary RDBMS (Relational Database Management System) developed by Microsoft. It was initially introduced in 1989. MSSQL is primarily written in C and C++. Microsoft offers a variety of MSSQL editions suitable for the differing requirements of software development projects which may range from small data storage needs to enterprise level applications simultaneously accessed by millions of users. MSSQL was originally intended for Windows and is usually a part of the Windows environment.

Head To Head Comparison Between MySQL and MSSQL (Infographics)

Below is the top 9 difference between MySQL vs MSSQL

MySQL-vs-MSSQL-info

Key differences between MySQL and MSSQL

Both are popular choices in the market; let us discuss some of the major difference:

  • Both MySQL vs MSSQL work well on Linux and Windows environment. However, MSSQL was originally developed for windows platform while MySQL natively integrates with Linux and LAMP technology stack.
  • GNU GPL edition of MySQL is freely available with source code. Whereas MSSQL is a proprietary software, its use entails purchasing licenses which in turn costs significantly for enterprise applications with multiple databases.
  • Both MySQL vs MSSQL Server behave well with multiple programming languages. Both RDBMS can be integrated with Java, PHP, C++, Python, Ruby, Visual Basic, Delphi, Go and R. However, MySQL additionally supports certain programming languages like Perl and Haskel which make it more popular among a wide range of developer community.
  • MySQL supports a wide range of storage engines. In addition, a programmer has at his disposal an alternative to use a plug-in storage engine. In contrast, MSSQL offers only one storage engine. Thus, MySQL offers better flexibility in terms of storage engine.
  • MSSQL empowers users to avail the benefit of row-based filtering which is achieved in a database by database way. At the same time, filtered data is temporarily held in a separate database. In comparison, MySQL requires users to filter rows, tables or users by individual databases. Hence, the filtering mechanism used in MSSQL is more optimized.
  • In MySQL, data backup is a cumbersome process. Back-ups are usually taken as SQL statements, though, minimizes the chances of data corruption in upgrading one edition of MySQL to the other. But, execution of multiple SQL statements while taking backup restoration is time-consuming. On the other hand, MSSQL neither blocks the database during back-up nor does the developer required to bear a time consuming back process making it simpler and straight-forward.
  • MySQL does not allow users to interrupt a query execution midway i.e. once a SQL query has been fired it must run its course. While MSSQL users can control the query execution and bring it to halt before its completion. MSQL transaction engine gives this functionality to the developers.
  • Both MySQL and MSSQL stores data as binary collections. MySQL allows other processes to access and manipulate database files at runtime. However, MSSQL does not offer access and manipulation of its managed files. It constrains unauthorized access to the database binaries and securing the data integrity. On this count, MSSQL offers better security constraints than MySQL.
  • MSSQL server is available in multiple editions ranging from Enterprise, Express, Web, Standard, Business intelligence, and Workgroup. While MySQL is mainly available as Community and Enterprise editions.
  • MyISAM and InnoDB are the distinctive features of MySQL. These engines are configurable which allow the developer to perform very different design and programming. On the other hand, while creating a database programmer do not explicitly specify different engines.

MySQL vs MSSQL Comparison Table

The primary Comparison are discussed below:

 The basis of comparison 

MySQL

MSSQL

Parent company MySQL AB introduced MySQL Microsoft released MSSQL
License Open source version is governed by GNU GPL and the proprietary edition by Oracle Inc. A single proprietary edition is made available by Microsoft
Underlying language C, C++ C, C++
Platform Linux, Solaris, macOS, Windows, FreeBSD Microsoft Windows server, Microsoft Windows, Linux
Performance Offers robust performance for high-end applications Similarity in performance and speed
Database model Stores data as a table in rows and columns Stores data as a table in rows and columns
Inter-table relationships Use primary and foreign keys Uses primary and foreign keys
Scalability Flexible to handle increased transaction as the data size grows Scalable enough to adapt to the increased transactions
Major implementation Joomla, WordPress, Drupal, Google, Facebook, Flickr Microsoft, Stack Overflow, MIT, Brilium Inc.

 Conclusion

In summary, both MySQL vs MSSQL are enterprise-grade RDBSs which are widely used for data storage backend. Both MySQL vs MSSQL offer an equivalent level of performance and speed for high transaction applications. Although, both MySQL vs MSSQL can be deployed on any platform, however, MySQL has better integration on all major platforms. The cost is another consideration which is a primary motivation before selection of a technology stack, here again, MySQL has an edge owing to the availability of its open source non-proprietary edition.

Recommended Article

This has a been a guide to the top difference between MySQL and MSSQL. Here we also discuss the key differences with infographics, and comparison table. You may also have a look at the following articles to learn more –

  1. MySQL vs SQL Server – Top Differences
  2. CSS vs JavaScript: Amazing Differences
  3. CSS vs CSS3 – Amazing Comparisons
  4. MS SQL vs MYSQL
  5. Oracle vs MSSQL: What are the benefits
  6. Oracle vs OpenJDK: What are the amazing benefits
  7. MySQL vs MongoDB: Benefits
  8. SQL Server Interview Questions: Want to know the best questions
  9. Learn the 6 Differences of Cassandra vs MySQL
Popular Course in this category
SQL Training Program (10 Courses, 8+ Projects)
  10 Online Courses |  8 Hands-on Projects |  80+ 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
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

© 2023 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA

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

Let’s Get Started

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
EDUCBA

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

Forgot Password?

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