With an increasing number of businesses establishing an online presence, databases have become a crucial requirement for organizations of all shapes and sizes. A database is a collection of data in a layman’s words, organized and stored in the electronic form to ensure easy access, retrieval, manipulation, and management of business data.
Databases are pivotal to a business’s success because they help store the relevant data in a centralized location. Not just that, they also facilitate the communication of critical business information like customer profiles, employee profiles, product inventory, sales transactions, marketing campaigns, and so on. Also, databases ensure data security through various authentication mechanisms like user logins and access specifiers.
In this post, we’re going to talk about relational databases, with a special focus on two popular data management tools – SQL and MySQL.
What is a Relational Database?
A relational database refers to the database type that stores a collection of data items having pre-defined relationships. This database adopts the relational model, representing data as a set of tables with columns and rows.
In a relational database, each column within a table contains specific data and a field that stores an attribute’s real value. On the other hand, the rows within a table contain a collection of a particular object’s related values. Each row has a unique identifier known as the primary key. You can access the stored data without needing to reorganize the tables.
Relational databases follow integrity rules to ensure that data stored in the tables always remains accurate and accessible. For instance, an integrity rule specifies that duplicate rows aren’t allowed in a table. It will prevent the occurrence of rows containing the same data, thereby eliminating errors in the table.
SQL and MySQL are two widely used terms in enterprise data management. While they may sound like close relatives, they’re innately different. If you wish to work with relational databases, big data, business intelligence, and business analytics, you must know the difference between SQL and MySQL.
SQL vs. MySQL: What are they?
What is SQL?
Structured Query Language a.k.a., SQL is the standard language used to operate, manage, and access databases. By making minor changes in the syntax, you can add, retrieve, delete, or access data in different databases. The American National Standards Institute (ANSI) maintains that SQL is the standard language for managing a relational database management system, such as MySQL. It is owned, hosted, maintained, and offered by Microsoft.
You can use SQL to write programs for making any modifications to a database. Besides that, you can use SQL to create and modify database schemas. One of SQL’s greatest advantages is that you can use a single command to access multiple records within a database.
What is MYSQL?
MySQL was developed way back in 1995 by MySQL AB. However, now it is owned and offered by Oracle Corporation. MySQL is an open-source relational database management system that uses SQL commands to perform specific functions/operations in a database.
MySQL is written in the C and C++ programming languages. It is compatible with almost all major platforms, including Windows, Mac OS X, Linux, and Unix-based operating systems. It is also a core element of the open-source technology stack, LAMP (Linux, Apache, MySQL, and PHP). MySQL offers a multi-user access to databases.
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SQL vs. MySQL: What are the fundamental differences between SQL and MySQL?
Here are the primary differences between SQL and MySQL:
- While SQL is a language used for operating different relational databases, MySQL boasts of being the first open-source relational database in the early 90s.
- SQL is a query language, whereas MySQL is a relational database that uses SQL to query a database.
- You can use SQL to access, update, and manipulate the data stored in a database. However, MySQL is a database that stores the existing data in a database in an organized manner.
- SQL is used for writing queries for databases, MySQL facilitates data storing, modifying, and management in a tabular format.
- SQL does not have support for any connectors. However, MySQL comes with an integrated tool – MySQL workbench – for designing and building databases.
- SQL follows a standard format wherein the basic syntax and commands used for DBMS and RDBMS remain pretty much the same, whereas MySQL receives frequent updates.
- SQL supports a single storage engine, but MySQL supports multiple storage engines and also plug-in storage engines. Thus, MySQL is more flexible.
- In SQL, the server remains independent of the database, which means that you can perform other operations on a database during a data backup session. On the other hand, in MySQL, you can perform a data backup by extract SQL statements. However, unlike SQL, in MySQL, the server blocks the database during a data backup session, minimizing data corruption chances when switching from one MySQL version to another.
- In terms of data security, the SQL server is much more secure than the MySQL server. In SQL, external processes (like third-party apps) cannot access or manipulate the data directly. While in MySQL, one can easily manipulate or modify the database files during run time using binaries.
- SQL is not an open-source language. Naturally, if you experience any issue, you cannot expect community support. Instead, you’ll have to rely on Microsoft SQL Server support. Contrary to this, MySQL being an open-source platform, offers rich and robust community support.
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To conclude, the SQL vs. MySQL debate is an open-ended one that does not end in an either/or argument. Although there are many differences between SQL and MySQL, they can very well complement one another to cater to your relational database requirements. Essentially, the choice between SQL and MySQL boils down to specific needs like security, speed, scalability, and efficiency.
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Q1. What are the different types of databases?
A database management system is an application that is used to create and manage databases. Depending on how the different database structures are managed, database systems can be of various kinds. Now, there are two kinds of database structures, namely, flat-file database and relational database. And there are four kinds of database systems – relational databases, hierarchical databases, network databases, and object-oriented databases. There is also a substitute to relational databases, called NoSQL databases, which can be used to store and manage vast volumes of data that is either structured or unstructured. Relational databases are by far the most extensively used database structures.
Q2. Is MongoDB a relational database system?
MongoDB is a document-based database that is open source and used for managing and storing massive volumes of data. It comes under the segment of the NoSQL database and is non-relational in structure. This is the world's most popular non-relational database offering enhanced flexibility, horizontal scalability, and a dynamic schema design. MongoDB can operate across multiple servers (more servers can be added based on the requirement) and allows any of its fields to be indexed. This makes it especially suitable for storing hierarchical data. The structure of MongoDB remains unaffected by SQL injection and is up to a hundred times faster compared to relational databases.
Q3. Hadoop or MongoDB – how are they different from each other?
Both Hadoop and MongoDB have gained extreme popularity when it comes to handling Big Data. While there are various similarities in these two database systems, there are also specific differences in their approach towards handling data. While MongoDB is based on C++, Hadoop is a collection of Java-based applications. Hadoop was created not to be treated as an alternative to transactional relational databases. It was meant for supplementing RDBMS for data archiving practices. MongoDB stores data in the form of collections of data, while Hadoop comprises a software ecosystem, where the distribution of data is carried out by the Hadoop Distributed File System (HDFS).