Description: The Data Manipulation Language (DML) is a set of instructions that allows users to interact with data stored in a database. Its main function is to facilitate the retrieval, insertion, updating, and deletion of data, making it an essential tool for database management. Through specific commands such as SELECT, INSERT, UPDATE, and DELETE, users can perform operations on data efficiently and in a structured manner. DML is integrated within a database management system (DBMS) and is fundamental for developing applications that require access to large volumes of information. Its use is not limited to querying data; it also allows for the manipulation of the structure of the data, which is crucial for maintaining the integrity and consistency of information. In summary, DML is a key component in the database ecosystem, providing the necessary tools to manage and operate with data effectively.
History: The concept of Data Manipulation Language emerged in the 1970s with the development of the first database management systems. One of the most significant milestones was the creation of the relational model by Edgar F. Codd in 1970, which introduced the idea of using a structured language to interact with data. From this model, languages such as SQL (Structured Query Language) were developed, which became the standard for data manipulation in relational databases. Over the years, DML has evolved, adapting to new technologies and programming paradigms, but its essence has remained constant: to facilitate interaction with data.
Uses: Data Manipulation Language is primarily used in database applications to perform operations on data. This includes retrieving information through queries, inserting new records, updating existing data, and deleting obsolete records. Additionally, it is fundamental in the development of web and mobile applications that require access to databases, as well as in generating reports and data analysis. In various environments, DML is crucial for data management in information systems, enabling organizations to make decisions based on accurate and up-to-date data.
Examples: A practical example of using DML is an SQL query that retrieves all records from a customer table: ‘SELECT * FROM customers;’. Another example is inserting a new record into a products table: ‘INSERT INTO products (name, price) VALUES (‘Laptop’, 1200);’. Additionally, the price of an existing product can be updated with a command like: ‘UPDATE products SET price = 1100 WHERE name = ‘Laptop’;’. Finally, to delete a record, one could use: ‘DELETE FROM products WHERE name = ‘Laptop’;’.
