Databases are the core of any business or project in some form. Whether your business deals with data from customers, or simply generates its own big data during operation, making use of a database will inevitably become a key part of running it.

How you set up, manage and use your database presents a myriad questions, but one of the first is: should you use a relational or non-relational database?

What are relational databases?

In short, relational databases are used to store data which is structured into tables. They’re probably what you think of when you imagine a physical representation of a database – tables of rows and columns containing data sorted into fields. Multiple tables may also contain the same columns. Think of a relational database like a spreadsheet.

They’re also known as SQL databases as they use SQL – Structured Query Language – or a variant of it. SQL is used to make queries, update, edit, or delete data, or pull results from queries to the database. These are all made possible by the fact that it is based on a relational database.

What are non-relational databases?

Non-relational databases are more like Word documents. Rather than using a structured, table-based layout for their data, non-relational databases store data in collections depending on what that data is. They’re also known as NoSQL databases, or ‘not only SQL’, as they can use other query languages depending on their layout.

Whereas tables in a relational database need to be stored in a column/row layout, a non-relational database stores data in different ways, in a non-standardised format.

Pros and cons of relational databases

If your website or business handles well-structured data, a relational database is likely to be right for you. As the tables standardise the data, a relational database makes it easier to store, update and retrieve specific datasets using SQL queries. This data can be more easily formed into accurate reports as it’s all in one format. In a non-relational database, the data is unstructured, which can make it difficult to make sweeping changes to it or make accurate queries.

Another benefit of relational databases is that the different tables can relate to each other, with fields in one table being referenced in another table. This is referred to as normalisation, and helps to reduce data deduplication. This term means that redundant data is eliminated as much as possible – for example, if two of the tables in a database have a ‘customer name’ column, these can be linked together so the data will only need to be entered once and will remain the same across both when updated.

The relational database model is mature and widely recognised, so from a practicality perspective, it’s generally easier for developers to work with. SQL is a language often learned early by developers, so using a relational database will make it easier for them to integrate into working with your data.

Off the bat, it seems that a relational database makes the most sense. After all, it’s far easier to visualise the data and its relationships, as well as gather results from it. However, it comes with drawbacks.

Notably, if you want to be able to use a relational database efficiently, a considerable amount of thought will need to be put into its architecture before it’s built. While you might start with a fairly simple structure, you may also find that further down the line, more data is added in different formats that needs to be integrated into your tables.

You’ll find that without careful planning, maintenance and restructuring further down the line to accommodate new data types can become costly for a relational database – so keep this in mind when you’re still in the planning stages.

Examples of relational databases

  • MySQL
  • PostgreSQL
  • MSSQL Server
  • MariaDB

Pros and cons of non-relational databases

While you might think a non-relational database is ineffective at properly storing data, it all depends on the data you’re planning to work with. A non-relational database works well when you’re storing many different types of data that cannot be easily sorted into fields and rows.

Another advantage of non-relational databases is the speed at which they are capable of storing data relative to a relational database. A relational database has a predefined structure, so when you want to update a piece of data, the SQL query needs to find the appropriate column, then replace the data in the correct row. While this seems straightforward enough, a table could have thousands of columns and rows, so finding the correct location could take a considerable amount of time.

The unstructured nature of a NoSQL database means that when data needs to be updated at scale, the system doesn’t need to work as hard to add it. Each piece of data can effectively be appended to the end of each respective collection.

Non-relational databases have seen considerable growth in recent years in the big data industry. The sheer volume of data, as well as the variance in types (including text, values, and other media) make the speedier nature of non-relational databases well-suited to gathering data at scale. With the amount of different types of data being gathered, attempting to store all of it in a relational database would become cumbersome and the data would not be able to be processed at a fast enough pace.

Scalability is another key benefit of using a non-relational database. If you’re anticipating that your data needs will increase rapidly, a non-relational database might be suitable for the time being. They are less time-consuming as they don’t require the restructuring of a relational database when more types of data are added.

Examples of non-relational databases

  • MongoDB
  • Cassandra
  • Redis

Relational databases vs non-relational databases

As many decisions in computing do, deciding whether to use a relational or non-relational database boils down to what exactly you intend to use it for – both now and in the future.

If you’ll be working with data which is well-structured, such as transactional, ecommerce data, or user data, a relational database will be able to store it in a way that makes it easy to pull results or analyse later. Just ensure you carefully plan how your database will look to prevent costly restructuring down the line.

If you intend to work with data that will be changing often, has many varying types, or if there’s a large volume of it that you need to process quickly, a non-relational database might be right for you. A NoSQL database is also well-suited to smaller projects which are shorter term, as they take less planning and creation – allowing you to get started quickly.

To get started with setting up your database, Fasthosts Cloud Servers can give you the flexibility you need to support a relational or non-relational database of any size. You can easily scale your server as you grow and expand your database, and load it up with whatever option you think best suits you.