SQL vs MySQL - Key Differences Between SQL and MySQL

In data management, SQL and MySQL are very popular and widely used terms. Although they both have the term ‘SQL’ in them, they are not quite the same. So, what is the difference between SQL and MySQL? Today, we will be learning just that in this blog on SQL vs MySQL.

SQL vs MySQL
Updated on 27th Nov, 20 146 Views

If you wish to pursue the domains of Big Data, BI, and Business Analytics, you will inevitably come across SQL and MySQL. The following are the topics that we will be covering today to help you learn more about these two key terms in the world of databases:

To start learning about SQL and MySQL, you will first have to know about relational databases and RDBMS. So, here’s a quick overview.

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Relational Databases and RDBMS Overview

A relational database organizes and stores data items, which are in a structured format, into a set of tables with columns and rows that can be linked based on common data or pre-defined relationships between them. How does this help? With a single query, one can retrieve a completely new table from the data that is in one or more tables. This also allows a better understanding of the relationships between the data and the capability to make better decisions based on the insights generated.

Every table is divided into specific categories called fields. Each column under a field contains vertical entries or values. The rows contain a collection of related values for a particular object. Each row comes with a unique identifier called the primary key. If you want to access the stored data, you can do so without the need for reorganizing the tables.

As part of its integrity rule, relational databases make sure that the stored data is always accurate and accessible. One such instance is the elimination of duplicate rows in a table, thereby eliminating further errors in the process.

To understand the concept of RDBMS, you will have to first quickly understand DBMS. DBMS is a database program or a software system that catalogs, retrieves, and runs queries on data. It efficiently handles all the data and has the capability to allow data extraction or modification by users or other programs. MySQL, Microsoft Access, SQL Server, Oracle, RDBMS, Clipper, etc. are all examples of DBMS.

RDBMS, on the other hand, is a subset of DBMS and specifically designed for relational databases. It is an acronym for relational database management systems.

The key difference between RDBMS and DBMS is that RDBMS applications save data in a tabular form, whereas DBMS applications do it in the form of files.

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What is SQL?

In simple terms, SQL or Structured Query Language is a standard language used for storing and managing data in RDBMS. With SQL, users can add, access, retrieve, update, and delete data in relational databases and tables. With SQL, the database can be queried in several ways by using English-like statements. SQL is owned, hosted, maintained, and offered by Microsoft and is used by MySQL, SQL Server, Oracle, MS Access, and Informix as their standard database language.

One of the significant aspects of using SQL is that with a single command, one can retrieve multiple records in a database.

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What is MySQL?

MySQL is an open-source RDBMS owned by Oracle that performs specific functions/operations and manages relational databases through SQL commands. It is written in C and C++ and supports major platforms, such as Windows, UNIX, Linux, and macOS X. It can be installed on a server or even on a desktop.

MySQL offers the ability to tailor the source code as per requirements and grants multi-user access to databases. It is scalable, fast, and reliable, and it offers an easy way to start a low-memory/disk/CPU database. It is one of the core components of LAMP (Linux, Apache, MySQL, and PHP), which is an open-source web-service stack.

Check out the difference between NoSQL and SQL in our comparison blog on SQL vs NoSQL.

 

SQL vs MySQL: The Fundamental Differences

SQL vs MySQL Definition: SQL is a domain-specific query language, and MySQL is an RDBMS that uses SQL to retrieve data from its database.

SQL vs MySQL Operations: Through SQL, one can perform operations to retrieve and manipulate the stored data in a database. MySQL stores the existing data in separate tables in an organized manner.

SQL vs MySQL Functions: SQL is used to write queries for databases, whereas MySQL facilitates data storing, modification, and management in a tabular format.

SQL vs MySQL Format and Syntax: SQL follows a standard format, and the basic syntax and commands remain the same, while MySQL is updated frequently.

SQL vs MySQL Support: Apache Spark Connector for SQL does not come with any Microsoft support. MySQL, however, comes with the MySQL workbench as an integrated tool that helps in designing and building databases.

SQL vs MySQL Storage Engine: While SQL supports a single storage engine, MySQL can support multiple and pluggable storage engines that make it more flexible.

SQL vs MySQL Server and Database: The server remains independent of the database in SQL, which means that you can perform other operations on a database during a data backup session. But, in the case of MySQL, it is not possible as the server blocks the database. This minimizes data corruption when switching from one MySQL version to another.

SQL vs MySQL Data Security: SQL Server offers much more data security than MySQL Server. In SQL, external processes or third-party apps cannot have access to or manipulate the data directly. Whereas in MySQL, the database files can be easily manipulated or modified using binaries during the run time.

SQL vs MySQL Community Support: SQL, not being an open-source language, does not come with community support. Microsoft SQL Server support is the only way. MySQL, on the other hand, offers rich and robust community support because it is an open-source platform.

SQL vs MySQL Pricing
 

Difference Between SQL and MySQL in Tabular Form

Difference Between SQL and MySQL

To conclude, the SQL vs MySQL comparison cannot be a debate, but they are simply two innately different data management tools that are complementary to relational database requirements.

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