In database administration, SQL and MySQL are essential components. They can be used to store, manage, and query data by database administrators, backend developers, full-stack software engineers, and other staff members.
Both MySQL and SQL are well-liked programs for managing data. They should not be mistaken for one another, though. Even though “SQL” is part of their names, MySQL and SQL serve distinct purposes. To start with, MySQL is a group of tools for administering, querying, and implementing databases, whereas SQL is a database language.
Learn the differences between SQL and MySQL, as well as which is better for you, by reading this guide. Additionally, we’ll offer advice on selecting the top data management system (DBMS).
What Are SQL and MySQL?
Before diving into the SQL vs. MySQL comparison, let’s look at what SQL and MySQL are.
What is SQL?
Short for Structured Query Language, SQL is the standard language for maintaining and managing a database. Programmers, database administrators, and other information technology (IT) professionals can use SQL to:
- Add, update, alter, or delete data in a database
- Run queries against a database
- Create new databases
- Delete databases
- Create stored procedures in a database
- Set permissions on views, processes, and tables
- Manage multiple relational database systems, such as Oracle, Microsoft Access, MySQL, and SQL Server
SQL is widely recognized worldwide. It became a standard of the American National Standards Institute (ANSI) in 1986 and the International Organization of Standardization (ISO) in 1987. Accordingly, most database queries for fetching, adding, and manipulating data are based on SQL syntax.
SQL has four main sublanguages:
- Data query language (DQL) is used for running queries on databases and extracting information from stored data.
- Data control language (DCL) defines authorizations, access, and permissions for processes and users accessing the database.
- Data definition language (DDL) helps to codify a database’s schemas and structures. Programmers can use DDL to create a table or define data types.
- Data manipulation language (DML) is used to modify existing database components. For example, software engineers can use DML to insert records, delete data, and update values.
Advantages of SQL
There are a few benefits of using SQL. These include:
- Commonality: SQL is everywhere. Not only can you use it in multiple IT systems, but you can also use it with other languages, including Python and R.
- Speed: SQL also can function at a high operating speed.
- Simplicity: SQL is one of the easiest languages to master. Unlike most programming languages, SQL uses an English-like syntax.
What is MySQL?
MySQL is a relational database management system (RDBMS) that uses SQL. An RDBMS is a set of tools for implementing, querying and managing a relational database. As its name suggests, RDBMS stores data relationally or in tables. Each row is a record with a unique ID number, while each column holds data attributes.
Backend programmers and IT professionals use MySQL to store blog posts, plugin information, users, and other data. They can also use MySQL to:
- Implement a relational database in a cloud system or app’s storage system
- Create and implement security policies
- Manage users
- Facilitate database integrity testing
- Create data backups
MySQL can be used in any industry, from eCommerce and finance to healthcare and manufacturing. Many internet-critical apps and websites use MySQL for their backends, including:
MySQL vs. SQL Server
Because MySQL is often called MySQL Server, it’s often confused with another database management program, SQL Server. However, there are many differences between MySQL vs. SQL Server.
Firstly, MySQL is free, and the SQL Server is a commercial RDBMS. Secondly, SQL Server offers more capabilities and functions than MySQL, including 24/7 tech support, a SQL Server Migration Assistant (SSMA), and Extract, Transform, Load (ETL) functionality.
Advantages of MySQL
MySQL is extremely popular for several reasons, including:
- Widespread compatibility: MySQL is compatible with all major architectures and technologies, including macOS, Windows, Linux, and most cloud data platforms. As such, it can support a range of backends and programming interfaces.
- Ease of use: MySQL’s relational nature makes it easy to use, especially for beginners.
- Scalability: MySQL offers on-demand scalability for facilitating app management.
- Comprehensive transactional support: With features like unrestricted row-level locking, multi-version transaction support, and durable transaction support, MySQL is a perfect solution for keeping your data secure.
- Significant cost savings: MySQL Community Edition is free and open-source software operating under the GENU General Public License. You don’t have to pay a cent to get started with MySQL. However, you do have to pay for the other MySQL products, such as MySQL Enterprise Edition and MySQL Standard Edition.
- Multiple storage engines: Lastly, MySQL provides many storage engines for its tables, including MEMORY (HEAP), MyISAM, ARCHIVE, InnoDB, CSV, and FEDERATED. Users can operate these engines to store and migrate data to other applications, including non-SQL software like Microsoft Excel.
SQL and MySQL vs. NoSQL
When researching SQL and MySQL, you’re bound to come across NoSQL. Short for “not only SQL,” NoSQL refers to non-tabular databases that don’t use SQL and function differently from RDBMS, like MySQL.
NoSQL databases come in a variety of shapes and sizes, including:
- Document databases: These store data in documents like JSON objects. Each record has pairs of fields and values. Values can consist of various data types, including objects, strings, booleans, numbers, and arrays.
- Wide-column stores: These store data in rows, dynamic columns, and tables.
- Key-value databases: In key-value databases, each item contains values and keys.
- Graph databases: Nodes and edges get stored in graph databases. Nodes usually store data about places, people, and things, while edges store data about the relationship between the nodes.
The most common NoSQL database programs include:
- Apache Cassandra
- Apache HBase
- Apache CouchDB
NoSQL databases are best for:
- Agile development
- Massive datasets
- Flexible database expansion
- Data that constantly changes
- Modern applications like real-time streaming and microservices
- Storing semi-structured and structured data
- Scale-out architecture
- Cloud architecture
What Is the Difference Between SQL and MySQL Server?
As you can see, SQL and MySQL are two distinct concepts. SQL is a language for maintaining and managing databases, while MySQL is an RDBMS that uses SQL. We outlined some other differences in the table below.
To sum it up, SQL is a language for managing and querying databases, and MySQL is a program that lets users store, handle, modify and delete data in a relational database.
How to Decide Which One is Best for You?
Is SQL or MySQL better for you? Unfortunately, there’s no right answer to this question since SQL and MySQL are completely different. As covered above, SQL is a domain-specific language for querying and managing databases. You can only use it if you have an SQL platform or RDBMS like MySQL. Once you’ve chosen an RDBMS or SQL platform, you can use SQL to store, modify, organize, and retrieve data from relational databases.
Tips for Choosing the Best DBMS
MySQL isn’t the only DBMS available. The market contains many other options, including MongoDB, PostgreSQL, Microsoft SQL, and Oracle DB. What DBMS you choose can have a significant impact on your project, so here are some tips for making the right decision:
Look at the Types of Data You Have
First, you need to look at the types of data you have. If your data is simple, doesn’t change very often, and accuracy is crucial, you should use RDBMS like MySQL. An RDBMS tabular structure guarantees consistency, accuracy, and reliability.
However, if you have large quantities of diverse and complex data, consider using non-relational databases. NoSQL databases can store all kinds of data, including images, booleans, and documents. They also tend to be faster than relational databases since a query doesn’t need to view several tables to deliver an answer. Instead, it instantly produces a document or image.
For instance, a hospital may have a non-relational database where all patients have documents with all their information, from name and diagnoses to credit card information and address. Although all this information is in different formats, NoSQL can store it in the same document.
Consider Your DBMS’ Integrations
Before choosing a specific option, consider whether your desired DBMS can integrate with the rest of your tech stack. For instance, if you’re running Apache Hadoop, you should choose a DBMS that can easily connect to it. Otherwise, you will have difficulties exporting and deriving insights from data.
Determine Your Scaling Requirement
Next, you need to determine your scaling requirements. How much data do you need to store and manage? How much will your data grow over the next few years?
If you’re expecting exponential growth, pick a DBMS that distributes data across an entire cluster instead of on a single computer. Examples include NoSQL databases like MongoDB, Cassandra, and HBase, which scale horizontally instead of vertically. This means that they scale by distributing jobs across machines. In contrast, RDBMS like MySQL scale vertically, requiring CPU upgrades to process more data.
Consider Your Budget, Amount of Data, and Your Team’s Level of Expertise
Finally, you need to consider your budget, amount of data, and your team’s level of database expertise to make the right choice. If you have a small budget, small datasets, and a team with limited database expertise, consider getting open-source DBMS like MySQL, MariaDB, or SQLite. These DBMS tools are free to use and supported by a sprawling community of users and developers. If your team members have questions about the installation process, they can simply reach out to the community. They can also change the source code as needed.
On the other hand, if you have a large budget, tons of data, and your team has the expertise to set up and use a complex DBMS, consider getting a commercial DBMS like IBM DB2, SQL Server, or Oracle DB. These platforms offer more features than their open-source counterparts, including:
- On-demand technical support
- Frequent updates and security patches
- Built-in security features, including at-rest and in-motion encryption, data masking, role-based access, and extensive auditing
- Backup compression for cutting storage costs
- Continuous availability
- Horizontal and vertical scalability
- Ability to handle certain types of documents and data, such as XML
- Intelligent automation