What is a database?

When you use Google Maps to drive to work, the platform relies on its geospatial database to suggest the best route. Once you’re at your desk checking your inbox, the email server retrieves your messages from a vast database. And if you need to backup a file, you’ll probably store it in a cloud database like Google Drive or Dropbox.

These are just a few ways professionals interact with databases, often without even realising it. These tools power virtually every technology used by businesses, from attendance trackers to web applications.

So what is a database, exactly? In this article, we’ll explore the different types of databases and their applications in the business world.

A database is an electronic system used to store and manage an organised collection of data. Businesses use databases to securely store various kinds of data, such as:

Software developers have created many types of database management systems (DBMS) to handle different kinds of information. One of the most popular systems is MySQL, which organises data in rows and columns. By contrast, MongoDB can store unstructured data, such as images and audio files, that doesn’t fit neatly into tables.

No matter which DBMS you use, you can query — or search — it to quickly retrieve data. For example, if you have a database with 2,000 photos, you might use dates or keywords to locate the images you need. That way, you don’t have to spend time sifting through them all manually.

Of course, databases aren’t just convenient storage tools. They’re also the foundation of business data analytics. These digital repositories allow you to retrieve data to analyse with statistical methods and other tools. The insights you gain can lead to more educated business decision-making.

Suppose you want to analyse customer data to learn more about your client base. With a well-organised database, you can easily retrieve demographic data for each customer. Platforms like Microsoft Power BI and Tableau allow you to analyse this data and find patterns. For instance, if you notice that your audience is mostly Millennial women, you could launch a marketing campaign to appeal to this group and boost revenue.

The type of data you’re storing will help determine which kind of database to use. Here are a few common kinds of repositories that you may already interact with in your day-to-day activities.

Companies often gather data points that are related to each other. For example, you might collect your customers’ names and email addresses or employee IDs and salary information.

If you store all this information separately in a database, it would be like a vast soup of data, leading to absolute chaos. You’d have no way of knowing who the contact information belongs to, making it impossible to personalise your email marketing. And if you have a large team, you’d never be able to match salaries to the right employees.

That’s where relational databases come in. They store data neatly in tables with columns and rows. Every row contains a single record — such as a product or customer — while columns represent predefined categories. This format lets you easily identify and understand the connections between data points.

Here’s a visualisation of a simple relational database for employee data:

Database administrators and other professionals use Structured Query Language (SQL) to build and manage relational databases. This programming language uses schemas — or pre-determined rules — to organise data points into tables. It also lets you retrieve specific data, such as a list of Project Managers or employees earning less than £40,000.

While SQL allows you to build a relational database model from scratch, you can also use pre-built systems like MySQL, PostgreSQL, and Microsoft SQL Server (MSSQL). They all use tables to organise data but have different features and limitations. For example, MySQL is a completely free open-source tool, while MSSQL requires you to pay for a licence to access all the features.

NoSQL may seem like the opposite of SQL, but it actually stands for “not only SQL.” These database management systems are perfect for handling unstructured or distributed data.

Structure is one of the biggest differences between SQL and NoSQL databases. While SQL databases use predefined tables, NoSQL databases have flexible schemas, allowing them to manage non-relational or unstructured data with ease. For example, in a document database, you might store blog posts and their metadata in JSON format. This approach lets you organise posts with various types of content effectively.

NoSQL databases are also easier to scale than SQL systems, making them a popular choice for managing big or complex datasets. This can include sensor readings from the Internet of Things devices, social media posts, and other data sources that can’t fit into tables.

Like SQL, NoSQL has many established systems with different data models. For instance, Cassandra stores information in columns, while MongoDB uses a document-based format.

While SQL and NoSQL are the most popular DBMS, they’re far from the only options.

Graph database systems like Neo4j organise data with nodes and relationships. These intricate networks can help you uncover connections between items that might otherwise get overlooked. For example, you could use a graph database to analyse the relationships between customers and products and offer personalised recommendations.

On the other hand, an object oriented database stores data as objects, consisting of properties and methods, or actions you can perform with the objects. In a grocery store database, for instance, a “product” object could have the properties “name” and “expiration date.” Each object could also have methods like “updateInventory” or “checkExpiration.” Popular object oriented databases include db4o and Objectivity.

Meanwhile, hierarchical databases use tree-like structures with parent-child relationships to organise related data points. A grocery store could create parent records for different departments, with child records representing individual products. One of the most well-known hierarchical databases is IBM’s Information Management System.

Even the smallest databases can have surprisingly complex structures. Every database system includes these key components:

All databases depend on physical systems for data storage. This hardware includes computers, hard drives, and other equipment.

For cloud databases, this hardware is typically stored and managed off-site by the service provider. The most secure databases have multiple physical locations to reduce the risk of data loss from natural disasters and other catastrophes. Amazon alone has built over 100 data centers(opens new window) to contain its physical equipment.

DBMS tools like Oracle Database and MySQL bridge the gap between hardware and users. Database software allows you to control and access your data, even if you’re thousands of miles away from the physical computer system.

Databases contain raw information, known as data, and organise it into a usable format. There are many types of data, from audio files to text and transaction records.

Most databases also include metadata(opens new window), or “data about data.” It provides additional information about the dataset’s properties, such as the author and creation date of files.

Like most software, databases don’t “speak” English. Instead, you need to use a programming language to write commands in a format that a database can understand. For example, you could use SQL to query or delete data from a relational database.

A database management system has specific rules and processes to help you manage and operate it. These procedures often include guidelines for setting up the database and creating backups.

A database management system is software used to create, manage, and maintain databases. This technology lets you modify the logical structure — like by merging or separating records — without having to rewrite the entire database.

A DBMS also includes access controls to restrict what users can view or modify, improving data security. Plus, it has built-in features for data backup and recovery, giving you extra peace of mind.

You may assume that only tech professionals use databases, but that’s not true. This technology supports countless business functions in every industry.

Marketing and sales professionals often rely on customer relationship management (CRM) systems like Salesforce. These platforms let users store and manage contact information and other customer data.

Similarly, databases allow banks to process financial transactions almost instantly. If a customer swipes their debit card to pay for a meal, the bank's database checks their account balance and verifies they've entered the right PIN number. Based on this data, the database will approve or deny the transaction.

Supply chain management is another common application for databases. Companies can use a DBMS to track their inventory in real time, reducing the risk of over- or understocking products.

Finally, businesses in all industries can use databases for data analysis. A bank might analyse financial records to detect fraud, while marketers can gain insights about customer behavior and preferences.

While databases have become increasingly critical to business operations, they’re not always easy to manage. Here are a few common database challenges that you may encounter.

Databases often store sensitive data like credit card numbers and addresses. This valuable information can make them a prime target for cyber criminals — especially in industries that collect vast amounts of personal or financial data.

In 2024, for instance, hackers breached the Ministry of Defence’s payroll system(opens new window) and stole the bank details of UK military personnel. That same year, cyber criminals launched a ransomware attack on a medical diagnostics service(opens new window), disrupting operations at several London hospitals.While cyber attacks on databases are a serious threat, you can use many strategies to protect sensitive information. For example, you should always encrypt data when you’re transferring it between databases. Access controls like multi-factor authentication and biometric readers can also reduce the risk of data breaches. 

An organisation’s data needs can drastically change over time. For example, the amount of demographic data you collect may increase exponentially as you reach new audiences. That’s why it’s critical to choose a database system that can scale with your business.

Huge databases may handle hundreds or thousands of requests per minute, especially if they’re central to your operations. This high traffic can cause frustrating performance issues like bottlenecks and delayed queries.

Fortunately, there are many ways to speed up your database and keep it in top shape. This often involves using query caching to reduce the strain on the database and rewriting sluggish queries.

Even the most vigilant businesses can experience devastating database failures. For instance, a flash flood could wipe out your hardware, or a hacker might corrupt your software with malware. If you’re not prepared, these disasters could lead to catastrophic data loss.

Regular backups are key to protecting your valuable data. Choose database software that automatically backs up your information to secure locations. You could also use a distributed database to replicate your data across multiple servers in different locations. That way, you can recover quickly if one server fails.

If the worst case scenario happens, don’t panic. Database software often has built-in recovery tools to help you restore some or all of your lost information.

As businesses increasingly rely on data for every operation, databases have become an essential tool in every industry. However, many people don’t know how to use this technology effectively. According to the Multiverse Intelligence Report 2024, 42% of employees struggle to structure, prepare, and manipulate data.

Upskilling can help you expand your database knowledge and prepare to take on more data-oriented tasks. Get started with a Multiverse’s data analytics apprenticeship. You’ll gain hands-on experience as you learn how to develop data infrastructure and use data tools. The best part? You can keep working in your current role as you learn.

Ready to take the next step on your professional journey? Apply for a Multiverse data apprenticeship today(opens new window).