What is a relational database?

Relational databases are one of the most widely used technologies in modern data platforms. They power business applications, analytics systems, reports and dashboards across organisations of all sizes. Relational databases live on a Relational DataBase Management System (RDBMS) such as SQL Server but there are many other types of RDBMS like Oracle, MySQL and PostgreSQL.

For businesses investing in data analytics, data pipelines, and digital transformation, understanding relational databases is essential. They form the backbone of structured data storage and reliable data processing.

Let's take a look at what a relational database is, how it works, and why it plays a critical role in modern data strategies.

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What Is a Relational Database?

A relational database is a type of database that stores data in structured tables made up of rows and columns. Each table represents a specific entity, such as customers, orders, products, or transactions.

The key feature of relational databases is that tables are connected through relationships using keys. These relationships allow data to be joined, queried, and stored efficiently.

In simple terms, relational databases organise data in a structured and connected way.

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How Relational Databases Work

Relational databases use a schema-based design that defines how data is structured. Entity Relationship Diagrams (ERDs) are created to explain how tables and fields are related to each other. These are created from a process known as normalisation which is used to make sure that there is no duplication of fields and records in the database.

Core database components include:

• Tables - Data is stored in tables with defined columns and data types.
• Primary Keys - Primary keys uniquely identify each record in a table.
• Foreign Keys - Foreign keys create relationships between tables by referencing primary keys in other tables.
• Views - Views are essentially stored select statements that appear like tables when queried.
• Stored Procedures - You can chain together multiple statements and use if then statements to determine which processing should happen and when, all stored in a single procedure you can call.
• Constraints - Restrict values allowed to be stored in fields using a formula.
• Indexes - Speed up data access by creating various types of index on columns.

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Structured Query Language (SQL)

SQL is the language used to interact with relational databases and includes two types of statements that are used to query, update, and manage data and objects within relational databases. Data Modification Language (DML) is used for modifying data using statements like INSERT, UPDATE and DELETE where as Data Definition Language (DDL) is used for creating tables, adding columns and modifying objects. Whilst there are always rumours about SQL being phased out these have not come to pass. Other technologies like Link allow for interaction with databases through an object in .Net which can help protect from SQL injection attacks.

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Why Relational Databases Matter for Businesses

Relational databases remain popular because they provide reliability, performance, and consistency.

Business benefits include:

• Strong data integrity and accuracy
• Structured and organised data storage
• Fast query performance
• Support for transactional systems
• Compatibility with analytics platforms

They form the foundation of many enterprise systems but the most common are CRM, ERP and ticketing systems.

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Relational Databases and Data Pipelines

Data pipeline automation relies heavily on relational databases as both source and target systems.

With automated data pipelines, organisations can:

• Extract data from transactional systems
• Transform and standardise records
• Load data into analytics platforms
• Synchronise systems in real time
• Reduce manual data handling

Relational databases integrate seamlessly with modern ETL tools like SSIS and Azure Data Factory.

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Relational Databases and Data Integration

Most businesses operate multiple relational databases across departments and applications.

Data integration can help organisations:

• Connect data across systems
• Standardise schemas and formats
• Remove data silos
• Analyse data for insight
• Enable cross-system reporting

Data Integration unlocks the full value of relational data by integrating data sets from disparate systems. Without data integration you could not track a view on your website to a lead in your CRM and onto a paying customer in your finance system.

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Relational Databases in Cloud Environments

Modern relational databases are no longer limited to on-premise servers.

Cloud-based relational databases provide:

• Automatic scaling
• High availability
• Built-in backup and recovery
• Security and compliance features
• Reduced infrastructure management

Cloud adoption makes relational databases more flexible and resilient with multiple redundant copies of your data spread across regions and zones.

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Relational Databases vs Other Database Types

While relational databases are ideal for structured data, other database types also exist.

Relational databases are best suited for:

• Transactional systems
• Financial data  
• Customer records  
• Structured reporting  
• Business-critical operations  

They remain the preferred choice for many enterprise workloads. Other databases like graph, cube databases, document databases and of course NoSQL databases which use value pairs all have their own unique uses and benefits.

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Security and Governance in Relational Databases

Relational databases support strong security and governance controls.

These include:

• Role-based access control (RBAC)
• Encryption at rest and in transit
• Audit logging
• Fine-grained permission management

When integrated with modern Active Directory or Azure AD security and governance frameworks, they provide very secure enterprise data environments.

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Common Challenges with Relational Databases

Organisations may face challenges such as:

• Performance bottlenecks at scale
• Orphoned records
• Legacy system limitations (Technical Debt)
• Migration challenges to the latest SQL Server versions

Professional database administration and development services can help overcome these issues. A DBA can tell you if it's a memory issue, a code issue, a CPU issue, a storage performance issue or any of the other common types of problem a database can suffer from.

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Best Practices for Using Relational Databases

To maximise value, organisations should:

• Consult a DBA for database design
• Optimise database performance with indexes
• Implement strong security controls using RBAC
• Integrate with Active Directory (AD) or Azure Active Directory (AAD)
• Monitor system performance and tune code where required
• Maintain backup and recovery strategies

up to 95% of database performance issues are caused by poor design. Getting DBA resource involved as early as possible is key to avoiding the pitfalls in relational database design. These practices ensure long-term reliability.

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Business Benefits of Relational Databases in Automated Environments

When used correctly, relational databases deliver significant business value:

• Reliable transactional processing
• Flexible design
• Good data integrity
• Fast data retrieval
• Reduced operational overhead
• Highly available infrastructure options

Relational databases have been a solid database infrastructure technology for well over 30 years with the database normalisation process going back decades more.

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Final Thoughts

Relational databases remain a core component of modern data landscapes. They provide structured storage, reliable performance, and strong data integrity that support analytics, and business intelligence technologies.

By combining relational database platforms with data integration processes, cloud modernisation, and governance services, organisations can build scalable, secure, and high-performing data environments.

With the right strategy and support model in place, relational databases become a powerful foundation for data-driven decision making.