Relational databases
Definition, overview & context

As part of our blog series on database technologies, today we are delving into the world of relational databases. We focus on the specific characteristics, advantages and challenges of relational databases. This article highlights the central role of SQL (Structured Query Language), discusses the essential ACID principles for data integrity and stability, and examines the importance of relational databases in the modern IT landscape.

We offer a compact overview to make it easier to understand the profound connections and added value of this technology in various application areas, without going into too much detail.

Daniel Huber


Relational database management systems (RDBMS) form the backbone of structured data storage by organizing information in tables with defined relationships. This structure is reinforced by the use of primary and foreign keys, which enables efficient linking and querying of data across table boundaries. The central role of SQL (Structured Query Language) in interacting with these databases is underpinned by ISO and IEC standards, which ensures standardized and comprehensive data manipulation and retrieval [1][2][3][5].

SQL enables detailed and flexible data processing, ranging from the definition of data structures (DDL) to the manipulation of data records (DML) and queries (DQL) through to access control (DCL). This versatility makes SQL an indispensable tool for professionals working with relational databases, including data analysts, developers and database administrators. With its clear syntax and powerful query functions, SQL supports a wide range of applications and enables seamless integration with various programming languages. Relational databases such as MySQL, PostgreSQL and SQL Server Express rely on these principles to ensure data integrity and consistency, making them a reliable choice for complex data management tasks [6][7][8][9].


Relational databases are the foundation of numerous information systems whose robustness is based on four essential principles, known by the acronym ACID: Atomicity, Consistency, Isolation and Durability. These principles are essential for ensuring reliability as well as stability and provide a deep understanding of the effectiveness of relational database systems.

Atomicity ensures that transactions are treated as indivisible units that are either completely successful or leave no traces in the event of an error. This all-or-nothing strategy prevents erroneous transactions from negatively affecting the system.

Consistency ensures that transactions always transfer the database from one valid state to another without breaking the defined integrity rules. This principle protects the reliability of the stored information and serves as a safety net against data corruption.

Isolation ensures that transactions, even when executed simultaneously, do not interact in a way that produces unpredictable results. This avoids the occurrence of “dirty reads”, where changes to a transaction that has not yet been completed can be read incorrectly.

Finally, durability ensures that once changes have been made, they are retained even in the event of system failures or restarts. This consistency is crucial to prevent the loss of valuable data and to ensure the long-term reliability of the database system.

The implementation of these ACID principles in relational databases forms the backbone for the development and operation of secure and efficient information systems by ensuring high data integrity and stability. [16]


Relational databases form the core of data storage, management and retrieval in the current IT landscape. Their ability to efficiently visualize complex relationships between data sets makes them indispensable for a wide range of applications. From business software to e-commerce platforms and content management systems, relational databases provide a solid basis for ensuring clear connections between different data elements.

The definition of comprehensive integrity conditions and the guarantee of data consistency are key characteristics of relational databases that ensure the reliability of data in business-critical applications. These skills contribute significantly to the stability and efficiency of IT systems and support companies and organizations in data-driven decision-making and process design. [1][3][9]

Within the financial sector, the importance of relational databases should be particularly emphasized. They guarantee precision, security and the rapid availability of data, which are essential for financial institutions. Relational databases such as MySQL, PostgreSQL and Oracle Database are central to the management of complex transactions, customer information, trade data and compliance regulations. A striking application example in the financial sector is the management of credit portfolio information. Relational databases enable the detailed analysis of credit risks, payment behavior and customer profiles in order to make well-founded decisions regarding lending and risk assessment [17][18].

With the increasing shift towards cloud-based IT landscapes, banks are also seizing the opportunity to simplify their IT architectures. This step, often referred to as “application simplification”, leads to cost reductions and promotes digital innovation. A modernized architecture enables banks to adapt the successful strategies of FinTechs while at the same time meeting regulatory requirements [19].


Relational databases offer significant advantages that make them attractive for a wide range of applications, but they also face challenges, particularly in terms of scalability and complexity.


  • Data integrity and consistency: Relational databases guarantee the reliability and accuracy of stored data through strict integrity conditions. This feature is essential for systems that require error-free data.
  • Flexibility in queries: SQL as a query language enables the efficient retrieval and management of data. This flexibility makes it easier to obtain information and supports complex analysis requirements.
  • Broad application support: The suitability for applications with clear data relationships, such as business software and content management systems, makes relational databases a versatile solution. [10][12]


  • Scalability: Handling large amounts of data and scaling in distributed systems can present challenges. These limits influence performance and availability in large-scale environments.
  • Complexity in distributed systems: Managing relational databases in distributed systems can be challenging due to the need for data replication and synchronization. [11]

Weighing up these advantages and limitations is crucial when choosing the right database solution. While relational databases offer extensive benefits in terms of data integrity and query flexibility, the challenges of scaling and complexity in certain scenarios can draw attention to alternative database models, such as NoSQL, which offer specific benefits in environments with unstructured data and high growth.


With the exponential growth of data volumes and the increasing presence of unstructured data, the need for NoSQL databases has become established. Traditional relational databases, which are primarily geared towards structured data, are reaching their limits in the dynamic and diverse data world of modern applications such as social networks, e-commerce platforms and big data projects.

Due to their schema-free nature and horizontal scalability, NoSQL databases offer a flexible and efficient solution for dealing with the diversity and volume of current data sets. These features enable NoSQL systems to offer improved performance for specific requirements that go beyond the capacities of relational systems. This makes NoSQL databases an essential addition to database technology, paving the way for the upcoming article on “NoSQL databases” and providing the basis for a deeper understanding of their use cases and benefits [13][14][15].

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Daniel Huber

Daniel Huber