Relational databases

Storing data effectively is crucial for any organization, but it can be challenging. Managing large datasets with various attributes and meanings can get confusing. However, with the right formatting and database system, your data can be displayed intuitively, with relationships and connections highlighted clearly.

Discover what relational databases are and how Micron’s advanced memory and storage solutions provide the robust foundation needed for optimal database performance and reliability.

What is a relational database?

Relational database definition: A relational database is a type of database structure based on relations between specific items within the database.

Databases are computational systems where users store large amounts of data, usually organized by categories and purposes. Relational databases build on that foundation, organizing data based on the relationships between data points.

The relationships are predefined when the relational database is built, so relational databases categorize data into groups that are helpful to the user. When data is fed into the database, it is processed and categorized into tables where the relationships are stated.

Instead of operating on a two-dimensional table system, with one table housing your key data, relational databases add additional dimensions to outline relationships among the data. This structure creates a more holistic view of the data contained within the database and allows users to extrapolate valuable conclusions more easily from the data by investigating the relationships.

It is important to have a relational database management system (RDBMS) when working with complex relational databases. An RDBMS gives users the capability to create, update and use their relational databases. A wide range of RDBMSs on the market offer varying levels of control and oversight.

How do relational databases work?

Relational databases work by connecting common features, labels and attributes among related tables within a database. Traditional databases are organized hierarchically, whereas relational databases allow more complex relationships to be denoted between data points.

The way that relationships are built and defined between tables within relational databases is through keys. All tables have a primary key, which is a unique identifier. Primary keys can be related to foreign keys, which refer to the primary keys of other tables within the database. By connecting primary and foreign keys, intertabular relationships are constructed.

The standard programming language used when working with relational databases is Structured query language (SQL). Using SQL allows the administrator to add, update and delete data very simply, with a few lines of code.

What is the history of relational databases?

Relational databases have been an established technology for a while, with origins in the 1970s and strong development in the late 20th century. In the 21st century, they have become a mainstay in data management across a wide range of industries.

• Prior to 1970, early database management systems: Before relational databases were devised, hierarchical databases could be managed with database management systems to allow administrators to organize large amounts of data. These systems form the basis of the RDBMS.
• 1970, conceptualizing database relationships: Edgar F. Codd published a paper in 1970 theorizing relational databases. This paper proposed that data could be arranged based on relationships between attributes.
• Early 1970s, development of SQL: With more research being dedicated to developing relational databases, SQL was developed in the early 1970s.
• 1979, first commercial RDBMS: Oracle released the first commercially available RDBMS in the late 1970s, opening the technology up to real-world use.

With more development through the 1980s and 1990s, relational databases were well-established by the 2000s and in common commercial use.

What are key types of relational databases?

Relational databases are a specific type within the broader category of databases. To understand their unique characteristics, let us explore what different types of databases exist and how relational databases stand out.

• Relational databases store data in tables, with individual data points having attributes and categories that are interconnected to show relationships among the data.
• Key-value databases store data in dictionaries, with each data point listing its value.
• Document databases store data in documents, keeping them in file types like JSON and XML, maintaining it as semi-structured data.
• Graph databases store data in graph format, using visual formatting to show relationships between the data and data properties.

Similarly, while relational databases are a subset of their own, users can choose from a range of relational database management systems. These RDBMSs include MySQL, Oracle database,​ ​PostgreSQL, SQLite and MariaDB. There are also​ ​NoSQL databases, which do not use SQL only.

How are relational databases used?

Relational databases are a smart way of formatting and storing data, offering an intuitive user interface. With this usability in mind, as well as the data storage solution it provides, relational databases have a wide range of use cases across varied industries.

Relational databases can be used to streamline business marketing plans, especially customer relationship management. Many customer relationship marketing (CRM) systems use relational databases to track complex data about customers, linking how customers of certain demographics might interact with platforms and services. This use offers businesses a deeper understanding of their customer base.

Within the healthcare industry, data storage is crucial for long-term patient wellbeing. Relational databases can monitor interconnected aspects of patient health and medical history. With relationships among medical data being highlighted within the database, these systems enable more intuitive diagnoses. These databases also allow medical professionals to check patients’ wider medical histories to ensure a holistic view.

The finance industry also uses relational databases to manage and monitor transactions from individual users. A database of users’ behaviors relating to their finances makes it easier to identify anomalous transactions.