By : Richard Peterson
Updated
Key Difference between Rows and Column
- A row is a series of data put out horizontally in a table or spreadsheet, while a column is a vertical series of cells in a chart, table, or spreadsheet.
- Rows go across from left to right. On the other hand, Columns are arranged from up to down.
- In a spreadsheet such as MS Excel WPS, LibreOffice, or Google Sheets, the row heading is indicated by numbers, whereas column headings are denoted by letters.
- You can define the row as an order in which objects are placed alongside or horizontally, while you can define a column as a vertical division of objects based on category.
- In the database, information like name, gender, and names, are placed in the rows, while the column contains information about someone who you are mentioning in the rows.
What is Row?
A row is a series of data placed out horizontally in a table or spreadsheet. It is a horizontal arrangement of the objects, words, numbers, and data. In Row, data objects are arranged face-to-face with lying next to each other on the straight line.
What is Column?
A column is a vertical series of cells in a spreadsheet, chart, table, or spreadsheet. It is an arrangement of figures, facts, words, etc.
Columns are mostly placed one after another in the continuous sequence. In a table, columns are mostly separated from each other by lines, which help to enhance readability and attractiveness.
Difference between Row and Column
Here are the main differences between Rows and Columns
| Row | Column |
|---|---|
| A row is a series of data banks put out horizontally in a table or spreadsheet. | A column is a vertical series of cells in a chart, table, or spreadsheet. |
| Rows go across left to right | Columns are arranged from up to down. |
| In a spreadsheet such as MS Excel WPS, LibreOffice, or Google sheet, the row heading is indicated by numbers. | In spreadsheet programs like excel, LiberOfifce column headings are denoted by letters. |
| Total number of Row is placed in the extreme right corner of the respective Row. | The total numbers of the column are shown at the bottom. |
| You can define the Row as an order in which objects are placed alongside or horizontally. | You can define a column as a vertical division of objects based on category. |
| A stub that is the farthest left part of the table describes the Row. | A caption that is the topmost of the table describes the column. |
| In DBMS, rows are known as records that contain fields. | In DBMS, columns are called fields which contain the collection of characters. |
| In a matrix, the horizontal arrays are also called rows. | In a matrix, the vertical arrays are also called columns. |
| In the database, the information like name, gender, names, are placed in the rows. | The column contains information about someone who you are mentioning in the rows. |
Row Examples:
Here are real-life examples of Row:
- The children are standing one after another.
- Group of people standing in a row at the back of the room.
- Building a row of houses alongside the river.
- Students are standing on the front row of the stalls.
Column Examples:
Here are real-life examples of the column:
- Weekly recipe Item
- Pillar in the front of a building
- A facade with marble columns
When to Use Row-Oriented Storage
Here are some common uses of row storages:
- Row-oriented storage is good if you need to touch one Row.
- This type of storage is also beneficial when most columns of a row need to be read or written.
- Reads are done page-wise so not many rows may fit on a page when rows are big
- Pages are normally not filled, which leads to reading lots of unused and unwanted areas.
- Row storage should be used when recorded headers need to be read too but do not contain actual row data
When to use Column-oriented storage
Here are some common uses of column storage:
- Column helps you to make a side-by-side comparison between two columns.
- Column-oriented databases primarily work on columns
- It is benefited if you want to store the value of a single column
- It helps array-processing the value of a column
- It helps you to improve the performance of queries that only touch a small amount of columns.
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