A relational database stores and connects data in tables and columns, emphasizing the relationships between the data. Relational databases are intended for data that’s structured and connected. Relational databases can be set to automatically update data if one instance of it is edited or changed; the other related data will receive real-time updates. People often use relational databases and relational database management systems (RDBMS) interchangeably.
Characteristics of relational databases
Relational databases use Structured Query Language (SQL) to work with data, tables, and columns. SQL queries, or commands, are used to add and edit data within a table. A computer or server on which the database system is installed pulls pieces of data from storage (such as an SSD) into memory for processing.
Relational databases store related pieces of data together in groups called clusters; clustering data reduces the number of queries required to pull data, because similar data is already arranged close together.
Relational databases are not always designed for extremely large-scale or high-performance data processing. Depending on the needs of the business using one, relational databases may be a little sluggish. Though they’re helpful tools for storing and retrieving data, relational databases can slow from all of the complex relationships between tables, columns, and pieces of data: eventually, all of those add up and can affect performance.
Non-relational databases are referred to as NoSQL databases. This doesn’t mean that they never use SQL, however. These databases are more flexible; the data doesn’t have to be as organized and structured, and it isn’t arranged in related tables.
One important aspect of relational databases is their integrity. This can include security (is the data safe from unauthorized access?) but is much broader than that. Database integrity asks questions like:
- Is the data stored in the database consistent? Or does it look different in different instances? Has it been corrupted through bit errors or other failures?
- Is the data still accurate? Sometimes, data is entered incorrectly into a database.
- Has the data been compromised?
This is particularly important for businesses that handle a large amount of sensitive customer data. Maintaining database integrity is also important for complying with regulations: for proper compliance, data needs to be whole, accurate, and accessible.
Database integrity is a very similar term to data integrity; it’s slightly different in that it refers specifically to databases.
There are many available database software and management systems. Six of the best-known are Microsoft SQL Server and Azure, Oracle, Amazon RDS, MySQL, and IBM Db2.
- Microsoft Azure SQL Database offers relational and non-relational database options. Azure SQL Database is flexible; it offers single database options and pools of databases that can share computing resources.
- Microsoft SQL Server is great for businesses that need to pull data from a database for multiple applications to use. It’s available in the cloud and on-premises. SQL Server can also run with Azure.
- Oracle is one of the most popular, well-known database providers in the world. They offer plenty of database options for businesses, including some that can connect to other database engines and third-party software.
- Amazon RDS offers six different database engines that work with it.
- IBM Db2 uses artificial intelligence in its family of database software. Db2’s relational database is not the only option for businesses. IBM first invented SQL in the 1970s.
- MySQL is an open source relational database management system that offers six different options for managing databases, some designed for the cloud.