Relational database

A relational database is a stored collection of digital information organized in table format to allow for an easier search and retrieval process. Early computer databases were capable of storing data, but searching for that information was often slow and complex. In 1970, a computer scientist developed a method to organize the data into rows and columns and established a searchable relationship among the data in the tables. A relational database not only aids in the search process, it also allows tables to be expanded and new data to be added more easily. Data tables can range from a few categories to upward of hundreds of thousands for large collections of information. In the modern era, relational databases are the standard means of accessing information and processing data transactions. The format is used to perform tasks from accessing bank and credit card accounts to making hotel reservations and online purchases.

Background

Prior to the growth of computer technology, most information was stored on paper and organized in various filing systems. In the eighteenth century, a system of cards with a series of punched holes was developed as an early form of automated data storage. The holes on the punch cards acted as "on-off" switches that carried a specific set of instructions. In 1890, American inventor Herman Hollerith developed a punch-card system to store data for the US Census Bureau. In the 1940s, many of the earliest computers used a variation of this system in the form of holes punched in strips of paper tape.

Prior to this, German inventors in the 1920s developed a way to store data on magnetic tape. Three decades later, researchers at the computer company International Business Machines (IBM) invented the hard drive, a method that could store more than twenty times the data of magnetic tape and made searching the data easier.

As the twentieth century progressed, technological advancements vastly improved computing capabilities. Compact discs (CDs), digital video discs (DVDs), and Internet-based storage—often referred to as the "cloud"—allowed for an increasingly large amount of data to be stored. To manage such enormous amounts of information, computer scientists needed to develop a more efficient way to organize, search, and retrieve the data.

Overview

The earliest computer databases were called flat databases, and they stored information in a long file consisting of a single row of text. Data values were separated by tabs, commas, or special characters such as a vertical bar (|). A database used to store bank records might have included first name, last name, address, and balance. For example, the following information might be stored in such a database:

John Doe, 123 Hill St., $1,000| Jane Doe, 42 Main St., $2,000| Tom Smith, 1 River St., $3,000|

Accessing the information required an advanced knowledge of computers and was often time-consuming. Users had to know where the information was stored beforehand and had to navigate through a string of text to find what they were looking for.

In 1970, Edgar F. Codd, a mathematician and computer scientist for IBM, developed a system that reorganized the stored data in tables consisting of rows and columns. Codd's relational model of data, as he called it, allowed users to access specific data without first knowing its location. The system was also easy to operate, which meant users no longer needed to be programming savvy to find the data.

In relational databases, each column contains a data category, sometimes referred to as a field. Each row contains a specific record of data related to the category defined by the column. For instance, each column in a relational database for a bank defines a single topic—known as a key—such as customer name, account number, address, balance, etc. The rows contain the specific data associated with the key—1234567, John Doe, 123 Hill St., $1,000, etc. A bank employee using the database would search for a relationship among the key and the rows of data. If a customer forgot his or her account number, an employee would search the table to view the number; a customer inquiry about available funds would prompt a search for data in the balance column. Relational databases can search for a link among data on several levels. It can look for how one row or key relates to another row or key, or it can see how one row or key relates to many rows or keys.

A relational database also gives users the ability to limit or expand the amount of data in a table to meet specific needs. Smaller companies may include only ten tables in a database, while bigger companies may have one thousand or more. The world's largest online retailer, Amazon, features a relational database with hundreds of thousands of tables. As new data or categories become available, relational databases can be easily modified to include the new information, simply by adding additional rows or columns to the tables.

A programming language called structured query language (SQL) manages relational databases. SQL was first developed in the 1970s and became the standard language used for relational databases in the early 1980s. The language is used for a variety of functions, including modifying database tables, adding columns or rows, and retrieving data from the tables. SQL commands used to change, insert, or delete data in tables use a programming language called data manipulation language (DML); commands used to create or modify database tables or structures use data definition language (DDL).

SQL commands are written as statements and typically include terms such as add, alter, create, delete, insert, select, truncate, and update. An SQL command to search a bank database for customers with account balances of more than $1,000 may look like this:

SELECT First‗Name, Last‗Name

FROM Balance

WHERE Balance > 1000

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