Computer Study

SQL Data Types

SQL (Structured Query Language) supports several data types that can be used to define the type of data that can be stored in a table column. Here are some of the common SQL data types:

  1. Numeric data types:
    • INTEGER: represents whole numbers.
    • FLOAT: represents decimal numbers.
    • DOUBLE: represents decimal numbers with more precision than FLOAT.
    • DECIMAL: represents decimal numbers with fixed precision and scale.
  2. Character and string data types:
    • CHAR: represents fixed-length character strings.
    • VARCHAR: represents variable-length character strings.
    • TEXT: represents large variable-length character strings.
  3. Date and time data types:
    • DATE: represents a date value.
    • TIME: represents a time value.
    • TIMESTAMP: represents a date and time value.
  4. Boolean data type:
    • BOOLEAN: represents a true or false value.
  5. Binary data types:
    • BLOB: represents binary large objects.
    • BYTEA: represents binary data in PostgreSQL.

These data types can be used in combination with other SQL keywords to define the structure and characteristics of database tables. It is important to choose the appropriate data type for each column based on the type of data being stored to ensure efficient data storage and retrieval.

Data Types in MySQL, SQL Server and Oracle Databases

MySQL, SQL Server, and Oracle are three popular relational database management systems that support SQL. Here are the data types supported by each of these systems:

  1. MySQL data types:Numeric data types:
    • TINYINT: represents small integers.
    • SMALLINT: represents medium-sized integers.
    • INT: represents large integers.
    • FLOAT: represents single-precision floating-point numbers.
    • DOUBLE: represents double-precision floating-point numbers.
    • DECIMAL: represents fixed-point decimal numbers.

    Character and string data types:

    • CHAR: represents fixed-length character strings.
    • VARCHAR: represents variable-length character strings.
    • TEXT: represents large variable-length character strings.

    Date and time data types:

    • DATE: represents a date value.
    • TIME: represents a time value.
    • TIMESTAMP: represents a date and time value.

    Boolean data type:

    • BOOLEAN: represents a true or false value.
  2. SQL Server data types:Numeric data types:
    • TINYINT: represents small integers.
    • SMALLINT: represents medium-sized integers.
    • INT: represents large integers.
    • FLOAT: represents single-precision floating-point numbers.
    • REAL: represents single-precision floating-point numbers.
    • DECIMAL: represents fixed-point decimal numbers.
    • NUMERIC: represents fixed-point decimal numbers with precision and scale.

    Character and string data types:

    • CHAR: represents fixed-length character strings.
    • VARCHAR: represents variable-length character strings.
    • TEXT: represents large variable-length character strings.

    Date and time data types:

    • DATE: represents a date value.
    • TIME: represents a time value.
    • DATETIME: represents a date and time value.

    Boolean data type:

    • BIT: represents a true or false value.
  3. Oracle data types:Numeric data types:
    • NUMBER: represents numbers with precision and scale.
    • FLOAT: represents floating-point numbers.
    • BINARY_FLOAT: represents single-precision floating-point numbers.
    • BINARY_DOUBLE: represents double-precision floating-point numbers.

    Character and string data types:

    • CHAR: represents fixed-length character strings.
    • VARCHAR2: represents variable-length character strings.
    • CLOB: represents large variable-length character strings.

    Date and time data types:

    • DATE: represents a date value.
    • TIMESTAMP: represents a date and time value.

    Boolean data type:

    • BOOLEAN: represents a true or false value.

Each of these systems may have additional data types or variations of the data types listed here, but these are the most commonly used ones. It’s important to choose the appropriate data type for each column based on the type of data being stored to ensure efficient data storage and retrieval.

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