Relational vs. Non-Relational Databases: What You Need To Know

Relational and non-relational databases are both common ways to store and categorize data. You can use either option depending on your needs. The most common question is whether you have structured or unstructured data. The amount of data also impacts your decision, as non-relational databases can handle more information.

Both types of databases are helpful for their specific causes. When you learn more about how they work and how they can organize your content, you’ll understand which one best suits your storage needs.

What Are Relational Databases?

A relational database uses rows and columns to sort data. You can link other tables with primary and foreign keys to keep everything structured. Relational databases contain structured data using Structured Query Language (SQL).

It’s easy to search relational databases due to their rigid structure. You can use search terms or constraints to find specific information or pull data for studies, analysis, and presentations.

One of the most popular relational databases is Microsoft SQL Server. Many companies already use Microsoft products for other aspects of their business, so using Microsoft SQL Server can help streamline their processes thanks to easy integration.

The most significant benefit of using relational databases is the organization and strict structure of the information. You can apply constraints that prevent data loss or overwriting and ensure a record has complete information before adding it to the database.

Examples of Relational Databases

Some of the most common relational databases are:

• Amazon Aurora
• IBM Db2
• MySQL
• PostgreSQL

What Are Non-Relational Databases?

Non-relational databases don’t use the standard table format to store data. Instead, they can use any structure that suits the information. These databases are ideal for storing items in various file types, like documents, emails, images, and videos.

While relational databases use SQL, non-relational databases don’t have that structure, so they’re NoSQL. This name doesn’t mean you can’t use SQL with a non-relational database, but rather that it’s Not Only SQL. There are various types of NoSQL databases, such as:

• Document
• Column-family
• Graph
• Key-value

Document stores pair keys with more complex documents than an SQL table. Column-family stores use rows and columns like a table, but there’s less structure in column names and format. Graph stores use graph structures to represent data. Key-value stores associate each piece of data with a separate key, like encyclopedia entries.

This variety of non-relational database structures helps you understand how the data can link and show patterns and relationships between entities. There are infinite possibilities with non-relational databases.

Examples of Non-Relational Databases

Since there’s less structure to non-relational databases, you can use many diverse options. Some of the most common include:

• Amazon DynamoDB
• Apache Cassandra
• IBM Cloundant
• MongoDB

How To Choose a Database

Understanding your data will help you choose the ideal database. First, consider if the information needs a rigid structure or not. That answer gives you an idea of how to move forward.

However, if you want a structure for your information but have a large amount, a non-relational database might provide better storage since it can handle more. You can still use SQL for the configuration. This database also gives you more room to grow, so you can continue storing data in one location, regardless of size or format.

You might think a relational database is best but think about your future needs before committing. If you might store unstructured data at some point, starting with a non-relational database is best. You can implement some structure into the format and handle any data type. A relational database can only handle smaller amounts of structured data.

For companies with small teams or limited resources to put towards storage, a relational database is ideal. It’s easier to learn and manage since it’s so structured. Non-relational databases require some programming knowledge since you’re taking data as-is and storing it instead of translating it into tables.

What Are the Best Database Options?

Using Oracle Database is an excellent choice because it’s widely available, affordable, secure, and flexible. If you find Oracle confusing to navigate, you or someone in your company can seek Oracle Database certifications. Earning these certificates demonstrates that you have the know-how to streamline data management through Oracle products.

Oracle databases allow extensive automation, simplifying the work you need to input while also reducing human error and increasing security. You can keep information in your own data center, in the cloud, or through the Oracle Cloud infrastructure.

There are several database options via Oracle, so you can use SQL, non-blocking queries, and multiversion read consistency to easily sort and access your data.

Of course, Oracle isn’t the only database provider. There are many options to consider, so it’s important to define your needs and requirements before choosing a database solution.