A relational database is a kind of database that uses rows and columns across tables to store data that is related to one another. Each row has its own unique key, or identity with columns containing different pieces of information related to that identifier. This primary key helps create a “relationship” between different tables. These data structures remain separate from physical data storage, which allows management of physical data storage without impacting the logical data structure.
Organizational reports such as inventory tracking, sales, and financial projections come from information gleaned from a relational database. For example, these databases can provide a snapshot of a customer and the use of certain products or services they use.
Important aspects of relational databases
Data consistency and integrity
Relational databases are the best at maintaining data consistency across various applications and database copies, or instances. These types of databases also use constraints such as primary keys, foreign keys, not NULL constraint, unique constraint, default constraint, and check constraints to help ensure data accuracy and reliability.
Use of SQL
As the American National Standards Institute standard, Structured Query Language (SQL) is supported by the most commonly used relational database engines. SQL can manage all the database features, such as adding, updating, or deleting rows of data. It can also retrieve subsets of data for transaction processing and analytics applications.
With a relational database, a transaction must be completed as a single unit and written to the database. If not, none of the individual components will go through. Each transaction is a “commit” or “rollback,” which leads to greater reliability and clarity.
ACID compliance required
Relational database transactions must be atomic, consistent, isolated, and durable (ACID) to ensure data integrity.
- Atomic defines all the database transaction elements and requires the entire transaction be successfully done or it’s invalid.
- Consistent means it must follow all the rules and restrictions.
- To be isolated, the transaction cannot be seen by others until it is committed.
- The durable aspect means that once data changes, it becomes permanent when the transaction is committed.
How is data in a relational database system organized for SQL?
Data in a relational database system is organized by storing data in tables. These tables are organized into columns and rows. Rows represent a collection of related values of one object or operation. Each row can have a unique identifier known as a primary key and joins to other tables and rows. The data can be accessed in various ways without reorganizing the database tables, usually by creating “joins” that relate the data points to one another.
These databases are often referred to as SQL databases because structured query language is what is used to access the data and create the joins.
Benefits of a relational database management system
- Meaningful information. By joining the tables, there is a better understanding of the relationships between the data and how the tables connect. SQL is also helpful because it provides the ability to add, count, group, and combine queries. It’s also capable of doing basic math and subtotal functions and logical transformations. It helps analysts because they can order the results by name, data, or column.
- Easy to use. A relational database doesn’t require convoluted structuring or querying. Hierarchical databases often require tedious architectural processes, but the relational database structure is simple and can be handled with effortless SQL queries.
- Painless access. Relational databases don’t require new code to access functions. Stored procedures – or blocks of code – allow easy access with a simple application call and also ensure that certain data functions in the application are done in a particular way. By using join queries and conditional statements, anyone can combine some or all of the related tables to get the necessary data.
- Accuracy. Data in relational databases is extremely accurate. That’s because multiple tables are related to one another using a primary key and foreign key. In other words, it’s not possible for data to be repeated.
- Reliability. The qualities of a relational database enable it to handle growing data amounts, updates, and deletes as needed. There are no limits on the number of rows, columns, or tables. Changes can be made to the database configuration without fear of crashing the data or other parts of the database.
- Better protection and recovery. Relational databases have easy export and import options, which enables easy backup and restoration. Exports can take place even when the database is running, which makes it simple to restore on failure. In addition, cloud-based relational databases can do continuous mirroring, which can ensure that the loss of data on restore is done in seconds.
- Reduced redundancy. With a relational database, the information for one customer appears in one place: the customer table. That means the order table simply needs to provide a link to the customer table.
- Database normalization. Normalization is the process of organizing data in a database, such as creating tables and setting relationships between various tables. There are rules set to protect the data but to make the database more accessible. With normalization, the aim is to eliminate any variances that can affect a table’s accuracy.
- Security. Unlike most other databases, it’s possible to tag certain tables as confidential in relational databases. If a data analyst isn’t cleared for a certain level of access, for example, then those tables are not available to that person. This may be important when working with outside contractors, or proprietary information that an organization wants to protect.
FAQ about relational databases
How does a relational database work?
Relational databases work by linking data and information from various related tables. This is done through a “key” that has a unique identifier. This key may be assigned to a row of unique data in a table and is known as a “primary key.” Some examples of a primary key include user names or serial numbers. The primary key can be included in a record at another table if the record is related to the main table’s primary record. When a primary key is added to the record in another table, this becomes known as a “foreign key.” This link between primary and foreign keys is what creates a relationship between datasets of various tables.
What are the logical structure of a relational database model?
The structure of a relational database model includes structures such as the data tables, views (which are subsets of tables, often for security/permission purposes), and indexes. They remain separate from the physical storage structures. To ensure accuracy and accessibility, relational databases follow integrity rules to prevent errors and duplication. Each database has a set of system catalog tables that describe the logical and physical structure of the data. There is also a configuration file that has the parameter values set for the database. Ongoing transactions and archivable transactions are in a recovery log.
What are types of additional databases?
The types of databases include NoSQL, which is beneficial for large, distributed data sets. This NoSQL database supports different data models such as key-value, document, columnar, and graph formats. When deciding between relational and non-relational databases, a key question is about the speed of the data access. Another kind of database is flat file, which has a single table of data that typically has text files. Relational data is often separated with a comma. A graph database is a NoSQL database that uses nodes and edges. These represent links between data relationships and can ferret out new data relationships. Such databases are often used for fraud detection or web recommendation engines. An object relational database contains characteristics of the relational database management system (RDBMS) and object-oriented database management system (OODBMS). The data is stored in a traditional database, which can then be accessed and changed using queries written in languages such as SQL.
What are the advantages of relational databases?
One of the advantages of relational databases includes easy categorization and storage of data that can then be queried and distilled to gain access to certain information. Another plus is eliminating data duplication and thereby gaining greater accuracy. Relational databases also make it easy to make complex queries using SQL, allow multiple users to access the same database, and provide greater security through restricted access if needed.
What are the disadvantages of relational databases?
One of the disadvantages of relational databases is that they have somewhat inflexible categories that require defined columns and certain data. These databases also tend to lack horizontal scalability, making it tough to handle them across several servers as the data sets grow and become more distributed. In addition, such databases demand more maintenance time as database personnel must manage and optimize the database as data is added.
What are examples of relational databases?
Some examples of a relational database include Oracle, MySQL, PostgreSQL, Microsoft SQL Server, MariaDB, and IBM Db2. Relational databases are often used by a customer relationship management system such as Salesforce to track customer transactions as part of a System of Record.
Find out how Aerospike’s non-relational database solutions can help you meet your business goals.