In a relational database context, column is referred to as a set of data values which are of a simple kind, a particular one for a row of the table. Column helps to provide the structure based on how the rows are made. It should be noted that when a column accommodates data values that are of a single type, it does not mean the column has only simple text values. Database of other kinds go beyond and allows the storage of data as a file on operating system. It is however different with column data as it covers only a link or pointer to the main file. Furthermore, database in most cases allows columns to have data that is more complex. Examples include video clips, images, documents etc. When it comes to relational database, column is equivalent to attribute. For example, when representing companies with a table, such table might have these columns

  1. ID
  2. Name
  3. Address line 1
  4. Address line 2
  5. City
  6. Postal code
  7. Industry etc

Every row would make provision for a data value for every column and afterwards be understood as data value of a single structure. In a more formal way, every row can be interpreted as a relvar which is composed of a set of tuples. These tuples consist of 2 items which are:

  1. The name of the relevant column
  2. The value that is provided by the row for that column

A table column serves as a means of representing all atributes of a column in a table. These include resizibility, width, minimum width and maximum width. A table column makes provision for slots for an editor and renderer which can be used to show and edit the values in a column. It is also quite possible to specify editors and renderers on a per type basis instead of a per column basis


With a table column, you can be able to make a representation of various things. Table column helps in keeping record of things.