![]() ![]() Id borrower_id lender_id book_id return_date In order to store them, we have designed a simple relational table with the following command: > CREATE TABLE book_transactions ( id INTEGER NOT NULL AUTO_INCREMENT, book_id INTEGER, borrower_id INTEGER, lender_id INTEGER, return_date DATE, PRIMARY KEY (id)) We will need to store all the book lending transactions. Let’s say we have an application where people can loan books. A tuple is represented by its attributes. MySQL is a relational database where all data is represented in terms of tuples, grouped into relations. Understanding Relational Databases Storage Let’s get started with the basics of how relational database store the data. All the benchmarking is done on a machine with 8GB RAM and with an i5 2.7 GHz processor. These are not limited only to MySQL but are also relevant with other relational databases like PostgreSQL. The examples described below are using InnoDB as MySQL engine. Photo source: According to the Stack Overflow survey 2018, MySQL is the most popular database among all users. Similarly, PostgreSQL has also seen a rise in popularity. ![]() MySQL has been a popular choice for small to large enterprise companies because of its ability to scale. We will be looking at how we can use relational databases according to our needs, and get the most out of them. Relational databases handle data smoothly, whether working with small volumes or processing millions of rows. ![]()
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