SQL
Structured query language (SQL) is a programming language for storing and processing information in a relational database. A relational database stores information in tabular form, with rows and columns representing different data attributes and the various relationships between the data values. You can use SQL statements to store, update, remove, search, and retrieve information from the database. You can also use SQL to maintain and optimize database performance.
Why is SQL important?
Structured query language (SQL) is a popular query language that is frequently used in all types of applications. Data analysts and developers learn and use SQL because it integrates well with different programming languages. For example, they can embed SQL queries with the Java programming language to build high-performing data processing applications with major SQL database systems such as Oracle or MS SQL Server. SQL is also fairly easy to learn as it uses common English keywords in its statements
History
SQL was invented in the 1970s based on the relational data model. It was initially known as the structured English query language (SEQUEL). The term was later shortened to SQL. Oracle, formerly known as Relational Software, became the first vendor to offer a commercial SQL relational database management system.
Process of SQL
When we are executing the command of SQL on any Relational database management system, then the system automatically finds the best routine to carry out our request, and the SQL engine determines how to interpret that particular command.
Structured Query Language contains the following four components in its process:
- Query Dispatcher
- Optimization Engines
- Classic Query Engine
- SQL Query Engine, etc.
A classic query engine allows data professionals and users to maintain non-SQL queries. The architecture of SQL is shown in the following diagram:
What are the components of a SQL system?
Relational database management systems use structured query language (SQL) to store and manage data. The system stores multiple database tables that relate to each other. MS SQL Server, MySQL, or MS Access are examples of relational database management systems. The following are the components of such a system.
SQL table
A SQL table is the basic element of a relational database. The SQL database table consists of rows and columns. Database engineers create relationships between multiple database tables to optimize data storage space.
For example, the database engineer creates a SQL table for products in a store:
SQL statements
SQL statements, or SQL queries, are valid instructions that relational database management systems understand. Software developers build SQL statements by using different SQL language elements. SQL language elements are components such as identifiers, variables, and search conditions that form a correct SQL statement.
For example, the following SQL statement uses a SQL INSERT command to store Mattress Brand A, priced $499, into a table named Mattress_table, with column names brand_name and cost:
INSERT INTO Mattress_table (brand_name, cost)
VALUES(‘A’,’499’);
Stored procedures
Stored procedures are a collection of one or more SQL statements stored in the relational database. Software developers use stored procedures to improve efficiency and performance. For example, they can create a stored procedure for updating sales tables instead of writing the same SQL statement in different applications.
What are SQL commands?
Structured query language (SQL) commands are specific keywords or SQL statements that developers use to manipulate the data stored in a relational database. You can categorize SQL commands as follows.
Data definition language
Data definition language (DDL) refers to SQL commands that design the database structure. Database engineers use DDL to create and modify database objects based on the business requirements. For example, the database engineer uses the CREATE command to create database objects such as tables, views, and indexes.
Data query language
Data query language (DQL) consists of instructions for retrieving data stored in relational databases. Software applications use the SELECT command to filter and return specific results from a SQL table.
Data manipulation language
Data manipulation language (DML) statements write new information or modify existing records in a relational database. For example, an application uses the INSERT command to store a new record in the database.
Data control language
Database administrators use data control language (DCL) to manage or authorize database access for other users. For example, they can use the GRANT command to permit certain applications to manipulate one or more tables.
Transaction control language
The relational engine uses transaction control language (TCL) to automatically make database changes. For example, the database uses the ROLLBACK command to undo an erroneous transaction.
What is MySQL?
MySQL is an open-source relational database management system offered by Oracle. Developers can download and use MySQL without paying a licensing fee. They can install MySQL on different operating systems or cloud servers. MySQL is a popular database system for web applications.
SQL vs. MySQL
Structured query language (SQL) is a standard language for database creation and manipulation. MySQL is a relational database program that uses SQL queries. While SQL commands are defined by international standards, the MySQL software undergoes continual upgrades and improvements.
What is NoSQL?
NoSQL refers to non-relational databases that don't use tables to store data. Developers store information in different types of NoSQL databases, including graphs, documents, and key-values. NoSQL databases are popular for modern applications because they are horizontally scalable. Horizontal scaling means increasing the processing power by adding more computers that run NoSQL software.
SQL vs. NoSQL
Structured query language (SQL) provides a uniform data manipulation language, but NoSQL implementation is dependent on different technologies. Developers use SQL for transactional and analytical applications, whereas NoSQL is suitable for responsive, heavy-usage applications.
Advantages of SQL
SQL provides various advantages which make it more popular in the field of data science. It is a perfect query language which allows data professionals and users to communicate with the database. Following are the best advantages or benefits of Structured Query Language:
- No programming needed
SQL does not require a large number of coding lines for managing the database systems. We can easily access and maintain the database by using simple SQL syntactical rules. These simple rules make the SQL user-friendly.
- High-Speed Query Processing
A large amount of data is accessed quickly and efficiently from the database by using SQL queries. Insertion, deletion, and updation operations on data are also performed in less time.
- Standardized Language
SQL follows the long-established standards of ISO and ANSI, which offer a uniform platform across the globe to all its users.
- Portability
The structured query language can be easily used in desktop computers, laptops, tablets, and even smartphones. It can also be used with other applications according to the user's requirements.
- Interactive language
We can easily learn and understand the SQL language. We can also use this language for communicating with the database because it is a simple query language. This language is also used for receiving the answers to complex queries in a few seconds.
- More than one Data View
The SQL language also helps in making the multiple views of the database structure for the different database users.
Disadvantages of SQL
With the advantages of SQL, it also has some disadvantages, which are as follows:
- Cost
The operation cost of some SQL versions is high. That's why some programmers cannot use the Structured Query Language.
- Interface is Complex
Another big disadvantage is that the interface of Structured query language is difficult, which makes it difficult for SQL users to use and manage it.
- Partial Database control
The business rules are hidden. So, the data professionals and users who are using this query language cannot have full database control.