SQL was initially developed at IBM by Raymond Boyce and Donald Chamberlin in the early 1970s. Originally called SEQUEL (Structured English Query Language), it was intended to manage and manipulate data stored in IBM’s experimental relational database system.
Later, the name was changed to SQL after ANSI (American National Standards Institute) adopted it as the standard language for relational databases in 1979. Today, Oracle is one of the key contributors and implementers of SQL, though the language itself remains an open standard used across many systems such as MySQL, PostgreSQL, and Microsoft SQL Server.
Key Facts:
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SQL stands for Structured Query Language.
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It is used to interact with databases.
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SQL is a database language for storing, retrieving, and manipulating data in a Relational Database Management System (RDBMS).
Basic SQL Commands
SQL provides a variety of commands for interacting with data. Here are a few fundamental ones:
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SELECT: Retrieves data from one or more tables.
SELECT * FROM employees; -
INSERT: Adds new data into a table.
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UPDATE: Modifies existing records in a table.
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DELETE: Removes data from a table.
Understanding these terms will help you get started with SQL more effectively:
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Database: A centralized system to store and manage data.
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Schema: The structure that defines tables, views, and relationships in a database.
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Entity: A real-world object or concept represented in the database (e.g., a customer or an order).
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Data: Individual records (rows) representing information in the table.
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DBMS (Database Management System): Software that handles the storage, retrieval, and updating of data in a database.
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DBMS provides services for:
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Inserting data
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Deleting data
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Updating data
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Accessing data
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Record: A single row in a table.
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Field: A single column in a table, usually of a specific data type.
SQL Queries
SQL queries are statements used to perform operations on the data, such as:
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Inserting new records
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Retrieving specific information
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Deleting unwanted data
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Updating existing data
Additional Concepts
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Database Schema: This outlines the logical structure of the database, including tables, columns, data types, relationships, and constraints.
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Constraints: These rules ensure the validity and integrity of the data (e.g., primary keys, foreign keys, NOT NULL constraints).
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Normalization: A process in database design that reduces redundancy and improves data integrity by organizing data into related tables.