Popular examples of relational databases include SQL, Oracle, MySQL, PostgreSQL, and MariaDB. This would not be as easily accomplished with a non-relational database. If we know the customer's name or email, we can run a single, simple command to pull down all data related to that customer. ![]() Using a relational database, we can relate all customer information back to each customer. Let's say we are a business that wants to organize our customers' billing information and survey responses. Next time when we look for that item, we can easily find it by simply searching for the type of the item on the dresser labels. After we store an item within a drawer, we label that drawer with the item's name or category, like socks or underwear. Within each drawer we can store a different type of item. Think of a dresser with many pullout drawers. Relational databases are so named because they store data in the form of tables, columns, and rows. SQL and other relational databases make it possible to easily manage and query for data. SQL stands for structured query language, and is the most popular relational database currently in use. This is where the relational and non-relational databases come into play. In order to store more complex forms of data, a database management system is needed. Tools commonly used as flat file databases include Microsoft Excel, Google Sheets, and Airtable. Flat file databases are great for storing simple data such as a monthly budget or a list of names. Data within a flat file database are organized through commas and tabs. ![]() Flat file databases store data in plain files such as. Now that you've got a good grasp of what a database is let's jump into the first type of database: the flat file database.
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