What is a relational database?
A relational database is a structured system for storing and managing data in tabular form, based on defined relationships between tables. Data is organized into rows and columns, linked using primary and foreign keys, and queried with SQL. Bissantz pulls data from relational databases for business intelligence and makes the information stored there available for analysis, reporting, and corporate management.
| Characteristic | Details |
| Category | Database architecture, IT infrastructure, data management |
| Application area | ERP, CRM, financial systems, business intelligence, e-commerce, accounting |
| Typical use cases | Data storage and management, SQL queries, reporting, KPI modeling, data integration |
| Related terms | SQL, OLAP, data warehouse, ETL, NoSQL, primary key, normalization |
| Benefits | Data integrity, consistency, scalability, redundancy avoidance, flexible querying |
At a glance
SQL as the standard language for queries, data manipulation, and analysis
High data integrity, scalability, redundancy avoidance, and flexibility for complex applications
Relationships between tables enable complex queries
Relational database: definition
A relational database is a structured data system that organizes information in tables. Each table consists of rows (records) and columns (attributes), and each column is generally assigned a specific data type. This structure is based on a relational model that relies on defined relationships between tables. Keys are used to establish connections between tables, enabling complex data queries and relationships to be handled efficiently.
Relational databases commonly use SQL (Structured Query Language) to manage and analyze data. Typical examples of relational database systems include MySQL, PostgreSQL, and Oracle Database, both in the cloud and on-premises within companies. They offer scalability, consistency, and security, making them ideal for business applications that require high efficiency and flexibility, such as business intelligence systems.
What characterizes a relational database? – Characteristics of a relational database
A relational database is characterized by several specific features in terms of its structure and functionality:
Table-based data structure: Data is stored in tables consisting of rows (records) and columns (attributes). Each table represents an entity, such as customers or orders.
Relationships between tables: Relational databases use primary keys and foreign keys to establish relationships between different tables. Each table contains at least one primary key that uniquely identifies each record. Foreign keys link records in different tables.
Normalization: Databases are often normalized to minimize redundancy and improve data integrity. This involves dividing tables into smaller, logically related units.
SQL as the standard language: Relational databases use the SQL language specifically developed for this purpose to filter, sort, and query data, allowing large volumes of data to be managed consistently and efficiently.
ACID properties: Database transactions should comply with the ACID properties (Atomicity, Consistency, Isolation, Durability). They ensure that transactions in a database are executed atomically (all or nothing), consistently (data remains valid), in isolation (simultaneous transactions do not interfere with one another), and durably (changes remain secure even in the event of failures).
What are the advantages of relational database systems?
The characteristics described above make relational databases a popular solution for a wide range of applications. Some of the key advantages of relational databases include:
Data integrity and consistency: Relational databases use strict integrity rules and ACID principles to ensure that data remains consistent and reliable, even in the event of system failures or errors.
Avoidance of data redundancy: Relational databases minimize redundancy through efficient structuring and linking of tables using primary and foreign keys.
Scalability and flexibility: Their clear structure and standardization make it easier to adapt relational databases to the needs of growing applications and companies.
How does a relational database work?
Relational databases operate primarily through SQL, enabling precise and complex data operations that are essential for efficient data management. SQL queries can range from simple data selections to complex data joins.
An important concept in the operation of relational databases is the JOIN operation, which makes it possible to combine data from multiple tables. JOINs are essential for establishing relationships between different records:
| JOIN Type | Description |
| INNER JOIN | Returns only records that match in both tables |
| LEFT JOIN | Returns all records from the left table, supplemented by matching records from the right |
| RIGHT JOIN | Returns all records from the right table, supplemented by matching records from the left |
| FULL JOIN | Returns all records from both tables, regardless of whether they match |
In addition, functions such as GROUP BY, SUM(), AVG(), COUNT(), and MAX() allow users to aggregate data and create summaries that are useful for data analysis.
To ensure the reusability of frequently performed operations, relational databases use stored procedures. These contain a series of SQL statements grouped into a single block and can be executed when needed with a single call.
BI tools such as DeltaMaster use mechanisms such as these, for example, to combine data from different sources and make it available for extensive analysis and data visualization. This makes it possible, for example, to calculate and display KPIs, reports, and dashboards from complex data structures.
What are common applications for relational database systems?
Relational databases form the backbone of many software solutions and IT infrastructures that need to store and manage structured data efficiently. They are therefore used across numerous industries and application areas. Typical examples include:
Data analysis and reporting systems: Tools such as Bissantz DeltaMaster use relational databases as data sources to aggregate and analyze structured information and present it visually in dashboards.
ERP systems (Enterprise Resource Planning): Relational databases store central information on financial accounting, purchasing, production, inventory management, and human resources. Well-known ERP solutions such as SAP ERP and Microsoft Dynamics use relational database models in the background to manage business processes consistently.
CRM systems (Customer Relationship Management): Systems such as Salesforce and HubSpot use relational databases to store customer data, interactions, campaigns, and sales opportunities in a structured manner and make them available for analysis.
E-commerce platforms: Shop systems such as Magento, Shopify, and Shopware use relational databases to manage product catalogs, user accounts, shopping carts, orders, and payment information.
Accounting and financial software: Applications such as DATEV, Lexware, and Sage use relational databases to manage accounting entries, charts of accounts, documents, and tax data.
What is a non-relational database? – The difference between relational and non-relational databases
When comparing relational and non-relational databases, i.e. SQL vs. NoSQL, several differences become apparent:
| Characteristic | Relational Database (SQL) | Non-Relational Database (NoSQL) |
| Data structure | Fixed tables with rows and columns | Flexible: documents, key-value pairs, graphs, columns |
| Query language | SQL – standardized, powerful | Database-specific, varies by type |
| Data consistency | High (ACID) | Variable (often eventual consistency) |
| Scalability | Vertical (more powerful hardware) | Horizontal (more servers) |
| Suitability | Stable, clearly defined data structures | Unstructured, dynamic, or very large volumes of data |
| Typical use cases | Financial systems, ERP, BI | Big Data, real-time applications, IoT, social networks |
Key-value databases store data as simple key-value pairs, making them ideal for caching and fast access.
Document-oriented databases store data in document formats such as JSON and offer flexibility in data structures.
Column-oriented databases store data in columns rather than rows and are designed for large volumes of data and real-time analytics.
Graph databases specialize in managing complex relationships between data points and are particularly well suited to network analysis.
Ultimately, whether a relational or non-relational database should be used depends on the specific requirements of the application, including the type of data and the complexity of the required queries. Both systems can often be used together to make optimal use of the strengths of both approaches.
Relational databases are well suited to applications with stable, clearly defined data structures, such as financial systems or relational data analysis, while NoSQL databases are particularly useful for modern applications that process large volumes of unstructured data or need to respond quickly to changing data conditions.
Bissantz and relational databases
Relational databases are a central foundation for working with the Business Intelligence software DeltaMaster. Almost all leading operational systems – from ERP and CRM to financial systems – are based on relational database models, from which Bissantz extracts structured data for analysis, reporting, and management.
DeltaMaster uses this structured data foundation to build KPI models, create reports, and make management-relevant relationships visible. Relational databases are not only read but also analyzed efficiently and flexibly using optimized SQL or MDX queries, particularly in combination with OLAP databases.
Typical data sources in the Bissantz BI context include Microsoft SQL Server, Oracle Database, and SAP HANA. DeltaMaster is designed to process even complex relational structures efficiently – for example through automatic JOIN generation, relational modeling aids, and intelligent aggregation of data at the KPI level.
Bissantz places particular emphasis on not exposing the complexity of relational data structures to users. The DeltaMaster user interface remains clear and intuitive, even when complex SQL or OLAP models are being processed in the background. The interaction between relational data storage and BI functionality is therefore essential for transparent, reliable, and comprehensible analyses across all areas of a company.
FAQ – frequently asked questions
A relational database is like a collection of interconnected tables – similar to several Excel spreadsheets linked through shared key columns. Instead of putting all information into a single table, data is logically divided: customers in one table, orders in another, products in a third – and connected through relationships. This makes it possible to answer complex questions efficiently without storing data multiple times.
SQL (Structured Query Language) is the standard language for relational databases. SQL can be used to query, insert, update, and delete data. SQL is so important because it provides a standardized, powerful language supported by virtually all relational database systems – from MySQL and PostgreSQL to Microsoft SQL Server.
Normalization is the process of structuring a database in such a way that redundancy is minimized and data integrity is maximized. Large tables are divided into smaller, logically related units and connected through key relationships. A normalized database is more consistent, easier to maintain, and less prone to errors – although highly normalized structures may require more JOIN operations for complex queries.
DeltaMaster connects directly to relational data sources such as Microsoft SQL Server, Oracle, and SAP HANA. SQL queries and intelligent aggregation transform structured data into business KPI models. The complexity of the underlying database structures remains completely in the background – users see clear reports, dashboards, and analyses.
Summary
Relational databases are the backbone of modern enterprise IT: They store structured data consistently, with integrity, and in a flexible, queryable form – based on SQL and defined relationships between tables. From ERP and CRM to Business Intelligence, they provide the reliable data foundation on which analyses, reports, and management decisions are built. DeltaMaster from Bissantz uses relational databases as a central data source – and translates their complexity into clear, comprehensible, and decision-relevant analyses for controlling.
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