Types of Databases

Introduction

Every company relies on data, be it global tech giants or the startup next door, which is crucial for providing customers with better and tailored services or products.

Remember when you sign up on a website, the next time you try to log in, you are automatically logged in without typing in your password?

For example, when you donate via any payment gateway and enter your details, you receive fundraising emails at specific intervals!

This is because all your personal information is stored in databases and can be retrieved by the organization against which you have entered the details.

But how are they stored? How are they retrieved by a pull request from the server in the back-end? Every website or application is connected to a database where information is stored.

Efficient data handling ensures that data is securely stored and can be accessed, modified, retrieved, updated, or deleted as required. This also helps in making informed decisions and supports operational efficiency.

Proper data management also helps comply with legal regulations such as GDPR, CCPA, HIPPA, PCI DSS, etc.

In the sections below, we will learn more about a database, types of databases, use cases, and how data is stored and managed on each database.

What is a Database?

A database is a data collection stored in an organized and structured format, typically in rows, columns, tables, etc.

The structured data is organized so that it can be easily accessed, managed, updated or deleted easily. Databases store static information like financial information, student records, customer information, employee data, etc.

Structured data like this makes it easy to access and update these records and facilitates easy data analysis and warehousing.

There are different types of databases, such as relational databases, object-oriented databases, hierarchical databases, and network databases, and they are used for a wide variety of applications, which we will discuss below.

What is a DBMS (Database Management System)?

A database management system is software that stores, organizes, manages, and controls database access.

A DBMS is the middle man (interface) between the end-user and the database, allowing for efficient data storage, retrieval, and manipulation.

In layman's terms, think of a DBMS as a super-organized digital cabinet. Imagine you have much information, such as contact lists, books, critical company files, and a shopping list.

Imagine you want a smart solution to store all this information neat and organised, find it without getting messy, update things whenever you require, and keep it safe from unauthorized access.

A DBMS software allows you to do this without digging through piles of paper or files. A common example would be when you search for a friend’s name in your contact list, and the phone uses a DBMS to find and display it quickly.

Another instance would be when you shop for something from any e-commerce site, the site’s DBMS stores and keeps track of what’s available, product prices, and your order history.

There are primarily 2 kinds of database management systems:

1. Relational Database Management System (RDBMS)

These databases store information in structured tables, such as rows and columns, using relationships between them. Ex - MySQL and Oracle DB.

2. Non-Relational Database Management System (NoSQL)

These databases store unstructured or semi-structured data with diverse data formats. Non-relational databases are great for storing dynamic and complex data. Ex - blog and social media posts.

Structured vs Unstructured Data

Before diving deep into the different types of databases, we need to understand the two primary types of data stored in a database. These data types strongly differ in storing, organising, or utilising them.

Structured data adheres to a predefined schema, which means it has a definite format in which the data is organized, stored, and managed in a database.

Structured data is stored in a tabular format, making it easy to search, filter, manipulate, and analyze using SQL databases. Examples include names, dates, customer IDs, financial records, etc.

On the other hand, unstructured data have no predefined schema and can include a diverse range of data types and formats. However, this also makes it harder to store and analyze without the help of specialized tools.

Examples include images, videos, emails, social media posts, etc.

What are the two primary types of databases?

Databases can be primarily classified under two major types:

1. Relational Databases - Relational databases store information in a predefined schema and an organized format, primarily in rows and tables.

This makes it much easier to pull out information using SQL (Structured Query language) for querying and managing data. Ex - MySQL, PostgreSQL, Oracle Database, etc.

2. Non-Relational Databases - Non-Relational Databases are much more complex and store data flexibly without a predefined schema or structured format. They typically store social media posts, blog posts, documents, graphs, etc.

These databases are best suited for storing semi-structured or unstructured data. Ex - MongoDB, Redis, Cassandra, etc.

Other types of Databases

In addition to the two primary types of databases, there are a wide canopy of other databases, which are as follows:

1. Hierarchical Databases

As the name suggests, a hierarchical database stores information in a tree-like structure. It is similar to a hierarchy of parent-child relationships where every parent can have multiple children, but each child has only one parent.

In technical terms, each record in the structure is called a node. Each parent node is further connected to a set of child nodes, creating a hierarchy of nodes.

In a hierarchical database, a parent node can have as many child nodes, but the vice versa is not possible. This makes the database rigid in terms of flexibility but allows for efficient and fast navigation.

Since the data structure is already predefined, searching within the hierarchy is quick and easy. The database uses pointers to connect parent and child nodes, which allows seamless data retrieval.

Below are a few of the areas where hierarchical databases are used.

Banking & Financial Institutions - For storing and managing customer information such as account details, branch details, and transaction history.

Healthcare - Managing financial records of patients in a structured format (patient ➡️visits ➡️prescriptions ➡️treatment).

Telecommunication - Manage data about subscribers, such as subscribed services and billing details.

2. Network Databases

In simple terms, a network database is hierarchical but with a major change. A network database allows for the flexibility of two-way relationships, meaning a child node can have multiple parent nodes.

Network databases allow a more flexible way to portray complex relationships with the data than hierarchical databases.

The records (nodes) are connected to multiple parent or child nodes, creating a many-to-many relationship between the data and not one-to-many, which is the case in a hierarchical database.

The architecture of a network database organizes data in a graph-like structure. As this model is typically used for representing complex relationships among data, they are best suited for systems which require extensive cross-referencing.

3. Object-Oriented Databases

An Object-Oriented Database (OOB) is a database where data is organized in the form of objects, similar to how objects are used in object-oriented programming.

Information stored in these databases is represented as objects with assigned attributes and instances. These objects can be referenced easily and called anytime without any external difficulty.

Hence, the load on the database is substantially reduced. The architecture of these databases is explicitly designed to support the management of complex data structures and hierarchies.

For the same reason, they are primarily used where manipulation of large chunks of unstructured and semi-structured data is required.

4. Relational Databases

These are the most widely used databases, which store information in structured and organized formats (rows and columns). In relational databases, every piece of information is related to each other via ‘keys’.

One important thing to remember in relational databases is that the data is stored in tabular formats, and every row of data in the database is connected to the other row via a ‘primary key’.

In the same way, one table is connected to the other via a ‘foreign key’. Due to the architecture and simplicity of relational databases have become increasingly popular in a wide array of applications.

Alongside, updating, managing, maintaining, deleting, and retrieving data is smooth and seamless in this kind of database, which makes it ideal for repositories for storing user data.

Another added advantage is that SQL interacts specifically with relational databases, which is much simpler and easier to learn and master. Scalability and traversing through data make this database stand out among other types

5. NoSQL Databases

In simple terms, NoSQL databases are the complete opposite of relational databases. Unlike traditional tabular data in relational databases, NoSQL databases store, manage and retrieve unstructured or semi-structured data.

The architecture of NoSQL databases includes an array of data structures different from the default structures used in relational databases. This makes certain operations faster in NoSQL.

In certain cases, data structures used by NoSQL databases are also more flexible than other types of databases. This makes it ideal for modern applications such as real-time analytics, content management, large-scale web applications, etc.

One of the core advantages of NoSQL databases is their scalability. They are explicitly designed for horizontal scalability, allowing them to handle large volumes of data by distributing the load across multiple servers rather than upgrading the existing server.

NoSQL databases use a distributed model for data storage, which reduces the risk of single points of failure. They store data in multiple formats, such as JSON, XML, or binary.

They are typically used in cases where data cannot be stored in tabular formats, such as to store social media posts, blogs, graphs, documents, etc.

6. Cloud Databases

A cloud database is a type of database that runs on a cloud computing platform, enabling users to access it over the internet.

Unlike traditional on-premises databases, cloud databases don’t require physical hardware or complex setup—the cloud provider manages everything. Popular examples include Amazon RDS, Google Cloud Spanner, and Azure SQL Database.

Cloud databases are highly scalable, meaning they can handle growing data and traffic seamlessly by adjusting resources dynamically. They also offer features like automated backups, high availability, and disaster recovery.

This translates to cost savings for businesses as they only pay for the resources they use.

For instance, a startup can store user data in a cloud database and scale up as its user base grows without worrying about infrastructure limitations.

7. Centralized Databases

A centralized database is a single database located in one system or location, accessed by multiple users and applications through a network. Think of it as a central hub where all organizational data is stored and managed.

For example, a company’s HR system might use a centralized database to store employee details, payroll information, and attendance records.

The centralized design ensures consistency and uniformity, as all updates and modifications occur in one place.

However, it comes with challenges, such as a single point of failure—if the central server goes down, the entire system becomes inaccessible.

Centralized databases are often used in organizations where maintaining control and consistency over data is critical, though they may require robust security measures to protect against unauthorized access.

8. Operational Databases

An operational database supports day-to-day operations, such as managing transactions, processing real-time data, and handling routine business tasks.

These databases are optimized for speed and reliability, making them the backbone of applications like banking, retail point-of-sale, and airline reservation systems.

For example, when you make an online purchase, the inventory, payment, and order details are all managed by an operational database.

Unlike analytical databases for decision-making and reporting, operational databases focus on quick updates, queries, and data consistency.

Technologies like MySQL, PostgreSQL, and MongoDB are commonly used for operational databases, ensuring smooth and efficient processing of high volumes of concurrent transactions.