Demystifying Azure's Relational Databases

Introduction: The Power of Data in a Digital World

Data is the digital fuel powering our modern world. Every click, transaction, form submission, or automated workflow generates data. Whether it’s processing financial records, validating workflows, or conducting audits, organizations—big and small—depend on data to function efficiently. But it’s not just about data generation; how we store, access, and process that data significantly impacts performance, security, and scalability.

This article aims to explore in depth how data is stored and managed using Azure’s relational database services—how they work, where they fit, and when to use them. To appreciate how far we've come, let’s first take a step back.

From Local Drives to the Cloud: A Brief History

In the pre-cloud era, data storage was physical and local—floppy disks, CDs, cassettes, external hard drives. While innovative at the time, these media came with serious limitations:

  • Limited capacity

  • High risk of data loss (due to theft, damage, or hardware failure)

  • No centralized access or real-time collaboration

  • Manual backups that were often neglected

These issues created an urgent need for scalable, secure, and resilient data storage solutions—needs that cloud computing eventually fulfilled.

But we’re here to talk about Azure relational databases, so let’s dive right in!

Enter Microsoft Azure

Microsoft Azure is one of the world’s leading public cloud service providers, offering over 200 services and holding approximately 21% of the global cloud market share. Azure excels in various cloud capabilities, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). It provides scalable computing resources, robust data storage solutions, advanced analytics, AI and machine learning tools, and a wide range of developer services. With a global network of data centers, strong security frameworks, and seamless integration with Microsoft products like Office 365 and Dynamics 365, Azure supports enterprises of all sizes in building, deploying, and managing applications efficiently in the cloud.

Understanding Databases and Their Types

What is a Database?

A database is a structured collection of data that can be easily accessed, managed, and updated. It provides the backbone for storing and retrieving information used by applications and users.

Types of Databases

There are two primary types of databases:

  • Relational Databases (SQL): Store data in tables (rows and columns) and enforce relationships between data. Ideal for structured data. Uses Structured Query Language (SQL) for operations.

  • Non-Relational Databases (NoSQL): Store data as documents, key-value pairs, graphs, or wide-columns. More flexible and suitable for semi-structured or unstructured data like JSON.

This article focuses exclusively on relational databases and, more specifically, how Microsoft Azure provides them.

What is a Relational Database Management System (RDBMS)?

An RDBMS is software used to manage a relational database. It provides tools for data storage, querying, updating, and administration. Examples include SQL Server, MySQL, and PostgreSQL. Azure offers these RDBMS technologies in managed forms to simplify deployment, maintenance, and scalability.

Azure's Relational Database Models: IaaS vs. PaaS vs. SaaS

Azure delivers relational databases through three key models:

  • IaaS (Infrastructure as a Service): Full control over the OS and DBMS. You manage patching, updates, and backups. (e.g., SQL Server on Azure VMs)

  • PaaS (Platform as a Service): Azure manages infrastructure, backups, updates, and scaling. You focus on data and apps. (e.g., Azure SQL Database, Azure Database for MySQL)

  • SaaS (Software as a Service): You consume data as part of a larger platform or application. (e.g., Azure Synapse Analytics)

Key Azure Relational Database Offerings

In this section, we’ll explore the main relational database services provided by Microsoft Azure, including their features, use cases, and the delivery models (IaaS, PaaS, SaaS) they align with. These offerings include:

  • SQL Server on Azure Virtual Machines (IaaS)

  • Azure SQL Database (PaaS)

  • Azure Database for MySQL (PaaS)

  • Azure Database for PostgreSQL (DaaS)

  • Azure SQL Managed Instance (PaaS)

  • Azure Synapse Analytics (SaaS/Data warehouse with relational capabilities)

Each of these services is tailored to different workloads, application architectures, and levels of administrative control.
SQL Server for Virtual Machines

This an IaaS RDBMS developed by Microsoft whose primary function is to store and retrieve data requested by application on Azure Virtual Machines. It gives you the same level of control as an on-premises deployment but in the cloud.

Key Features:

  • Full control over the OS and SQL Server configuration

  • Lift-and-shift migrations from on-premises

  • Ideal for legacy apps requiring specific SQL Server versions

  • Integration with Azure Backup and Azure Monitor

Use Cases:

  • Apps requiring full administrative control

  • Existing workloads migrating with minimal changes

  • Custom SQL Server configurations not available in PaaS

Azure SQL Database

This is PaaS solution that abstracts the nitty-gritty configuration of the SQL Server. It is a fully managed, intelligent relational database service built on the Microsoft SQL Server engine. It eliminates the need for managing hardware, patches, backups, and high availability.

Key Features:

  • Automatic backups, tuning, and scaling

  • Built-in high availability

  • Advanced security features (e.g., threat detection, encryption)

  • Integration with Azure ecosystem and tools

Use Cases:

  • Cloud-native applications

  • SaaS apps needing high availability and scalability

  • Businesses seeking reduced maintenance and overhead

Azure Database for MySQL

This is used to host a MySQL database in Azure. It's a fully PaaS managed database as a service offering that can handle mission-critical workloads with predictable performance and dynamic scalability.

Key Features:

  • Community edition compatibility

  • Auto patching and backups

  • Elastic scaling

  • Security with VNet integration and firewall rules

Use Cases:

  • Open-source applications using MySQL

  • Web and mobile apps (e.g., WordPress, LAMP stack)

  • Developers needing a quick-to-deploy MySQL environment

Azure Database for PostgreSQL

This is a relational database service based on the open-source Postgres database engine. It's a fully managed database-as-a-service that can handle mission-critical workloads with predictable performance, security, high availability, and dynamic scalability.

Key Features:

  • Community edition support

  • Built-in high availability

  • Fine-grained performance tuning

  • Integration with Azure services like Azure Data Factory and Power BI

Use Cases:

  • Applications built on PostgreSQL

  • Advanced data analytics and geospatial workloads

  • Developers needing open-source PostgreSQL with managed infrastructure

Azure SQL Managed Instance

A managed SQL Server instance that combines the benefits of PaaS with nearly full compatibility with on-premise SQL Server, making it a bridge between SQL Server on VMs and Azure SQL Database.

Key Features:

  • Near 100% compatibility with SQL Server

  • Managed backups, updates, and scaling

  • Supports cross-database queries and SQL Agent

  • Built-in high availability

Use Cases:

  • Migrating complex SQL Server apps to the cloud with minimal refactoring

  • Organizations that want PaaS benefits with high compatibility

  • Apps using features not supported in Azure SQL Database

Azure Synapse) Analytics

A powerful analytics service that combines big data and data warehousing capabilities. It supports SQL-based querying over large-scale structured data.

Key Features:

  • On-demand and provisioned resource models

  • Integration with Spark, Data Lake, Power BI

  • Real-time analytics on massive datasets

  • Built-in data ingestion and transformation

Use Cases:

  • Enterprise data warehousing

  • Real-time reporting and BI

  • Large-scale analytics across multiple data sources

Choosing the Right Azure RDBMS: A Quick Guide

NeedRecommended Service
Full control and lift-and-shift migrationSQL Server on Azure VM (IaaS)
Cloud-native, minimal managementAzure SQL Database (PaaS)
Full SQL compatibility with managed serviceAzure SQL Managed Instance (PaaS)
Open-source web stack (e.g., LAMP)Azure Database for MySQL (PaaS)
Advanced analytics with geospatial supportAzure Database for PostgreSQL (PaaS)
Massive-scale analytics and reportingAzure Synapse Analytics (SaaS)

Final Thoughts

Relational databases are at the core of modern enterprise applications. Microsoft Azure offers a wide range of relational database solutions to suit every workload—from legacy system migrations to cloud-native SaaS platforms and large-scale analytics pipelines.

By understanding what each service offers and when to use it, developers, architects, and IT leaders can make informed decisions to drive scalability, performance, and innovation.

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Written by

Olagunju Joshua Gbolahan
Olagunju Joshua Gbolahan