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Relational databases store and manage data in a traditional table format, with each piece of data organized into a row and a column. Columns hold the data of a single type or field, like first name, order number, or the image link of a product logo. Rows create the relationship between these data points. For example, rows can associate a first name to a last name and then to a user name, email address, and customer ID. Businesses use relational databases to maintain the data from their applications and ensure they always have access to critical customer information, product data, social data, and financial particulars like purchases, fulfillment, revenue, and expenses. These systems can range from desktop applications that create a small database on your machine to large enterprise-grade data stores. Almost all use a form of SQL as their query language, and most adhere to the ACID set of properties to ensure reliable transactions: atomicity, consistency, isolation, and durability.
Relational databases are generally chosen due to their simplicity in comparison to NoSQL databases, such as object-oriented databases, document databases, and graph databases. Those looking for a relational database solution with little budget also have options with free database software.
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Relational databases organize data in tables by rows and columns, where columns represent a single type of data (e.g., an order date), and rows relate multiple types of data to a single, unique identifier. Each row’s unique identifier is called a primary key. Multiple tables can be connected to each other using foreign keys, which are a particular column of the same type of data on two or more tables. This allows users to find vast arrays of interconnected data with ease. Relational databases software facilitates the building, maintenance, and usage of these tables.
Relational databases are not usually object-oriented, as they are built on creating relationships between pieces of data. Typically, relational databases are built on a querying language called SQL (Structured Querying Language). Relational databases software will almost always read SQL and use SQL syntax or similar. SQL’s syntax is very simplistic, and as such, it is one of the easiest languages to learn and use. Relational databases software is often built to follow the ACID (atomicity, consistency, isolation, and durability) transaction model to confirm that updates made to a SQL database are complete, accurate, and reliable.
Key Benefits of Relational Databases Software
Data Association — Relational databases are extremely powerful for storing and retrieving associative data. Be it e-commerce order details, patient information, stock tracking, or something more, relational databases excel in creating meaningful connections between a primary key and its describing information. Because they can be uniquely generated, primary key values are typically numbers, and values (e.g., full name, quantity, order date) are associated to that value by being stored in the same row on the table. This massively improves data organization for companies.
Targeted Query Results — By using relational database software, businesses can build vast, interconnected databases that quickly return important information, exactly as needed. Relational databases have a massive strength in being able to produce query results that span over numerous tables. By using join operations and table aliases, users can query across several tables at once to build an output of the exact data they require. This eliminates the need to store huge quantities of data on a single table. Instead, database administrators can build out as many tables as needed to better organize data, and those tables can be connected by foreign keys if any of the data needs to be associated.
Ease of Use — Relational databases are designed to be easy to build and even easier to use. At a fairly low learning curve, anyone in your company that could make use of relational databases tools would be able to use them with basic training on the software.
What makes relational databases software particularly beneficial is that it’s highly flexible and can be used by so many teams throughout a company. Below are some examples:
Finance and Accounting — Relational databases can be used to track payments and dues by associating a vendor ID, customer ID, or other unique identifiers to payment dates, payment amounts, check or order numbers, and more. All of this can be easily queried through relational database tools, and a complete transactional record can be created in a matter of minutes or even seconds. The ability to organize or isolate this data by, say, transaction date or personnel can greatly improve your finance associates’ efficiency.
E-Commerce — Internet prevalence and ease of use has made online ordering, from food pickups to clothes or machinery, not only simple but very widely used. Relational databases can store vast transactional data, including order date/time, customer name, payment method used, customer location, and more. Verifying an order’s correctness is a query away. Additional benefits for e-commerce come in that relational databases can store incredible volumes of information. Individual tables can store millions upon millions of entries at once without harming workflow.
Patient Tracking — Relational database tools offer immense value in health care because of the ability to relate so many data points to a single unique identifier. In health care, patients have hundreds of data points to describe their condition, including age, weight, blood pressure, and numerous others. By being able to associate all of those data points to a single unique identifier (e.g., a person’s patient ID), health care professionals—doctors, nurses, lab techs, database admins, and more—can have quick access to any and all relevant data.
Database Creation and Maintenance — Quickly create brand-new relational databases and modify them with ease.
Scalability — Relational database solutions grow with your data, so the only capacity you have to worry about is physical or cloud storage capacity.
Data Security — Relational database solutions include data security features to protect the data your business stores in its databases.
OS Compatibility — Relational database solutions are compatible with numerous operating systems, so your business won’t have to worry about the OS when creating databases.
Recovery — Whether a database needs to be rolled back or outright recovered, some relational database solutions offer recovery features in the event errors occur.
Unstructured Data — As noted above, there is a point where relational databases can struggle: handling unstructured data. Relational databases hinge on data being structured to properly create relationships between data points and data tables. If a company uses mostly unstructured data, they should consider perhaps a NoSQL database solution or a data quality software to clean and structure unstructured data.
Query Lag — Relational databases can store massive quantities of data, but with that advantage, you may find that relational database tools run queries a little more slowly on larger data sets. This is mainly due to the sheer volume of data being queried. In situations where queries might traverse significant quantities of data, try to query based on specific values whenever possible. Also, querying strings takes significantly longer than querying numerics, so focusing on numerics whenever possible may help improve search times.