base de datos relacional

Securing the Right Relational Database for Your Testing Needs

The emergence of relational databases years ago brought the possibility to standardize how data is presented and queried. Their great intuitiveness, efficiency, and flexibility have marked a particularly significant advancement in the current context where data have become crucial assets for companies and organizations.

While the earliest databases had unique structures that hindered efficient use, the relational database model came to solve problems associated with multiple and arbitrary structures.

Testing environments present specific challenges for companies: from data protection to finding quality data. Therefore, today we want to review what exactly a relational database structure is, its benefits for testing environments, and how to access them.

What Is a Relational Database?

A relational database is a type of database that organizes information into structured tables that are interconnected.

It is one of the preferred models for databases today and typically takes the following form: tables represent entities; information is stored in rows and columns, which represent the attributes or characteristics of the table. Each row represents an instance or record within the entity.

To be considered a relational database, there must be relationships between the tables. These relationships are established through primary keys and foreign keys.

  • A primary key is an attribute or set of attributes that uniquely identifies each record in a table.
  • A foreign key represents a reference to a primary key in another table, thereby establishing the relationship between the tables.

They are also characterized by adhering to four criteria for coherence following the ACID model: Atomicity, Consistency, Isolation, and Durability.

This database structure helps avoid issues like record duplication, in addition to ensuring referential integrity. This means the deletion of one record does not affect the rest, facilitating access to and recovery of information.

Therefore, it is the suitable option for handling large volumes of structured data in various contexts: from tracking inventories to storing customer information or e-commerce transactions, among other operations.

Relational databases are managed through systems known as relational database management systems (RDBMS). These systems provide specific tools and languages (such as SQL or Structured Query Language) for managing and processing the data stored in a relational database, ensuring its integrity and security.

The Structure of a Relational Database

The relational database model entails a separation between logical data structures and physical storage structures. This allows administrators to manage the physical data storage without impacting the logical structure due to access.

Operations are also divided between logical and physical operations in terms of data and structure manipulation, respectively.

Beyond this division in the macrostructure of the relational database, the following elements comprise it:

  1. Tables: the fundamental structure, representing a specific entity or concept (e.g., customers, products, or orders). A relational database can contain multiple tables.
  2. Rows: specific records or instances of the entity. For example, a customer table might have rows representing each individual customer and their associated attributes.
  3. Columns: represent the attributes or characteristics of the entity.
  4. Primary keys: an attribute or set of attributes that uniquely identifies each record in a table. Each table has a single primary key, and its role is to ensure the uniqueness of the records and establish relationships with other tables.
  5. Foreign keys: act as a foreign reference to a primary key in another table. They are used to establish relationships between tables and maintain referential integrity, linking the records of one table with the corresponding records in another table.

Benefits of a Relational Database

Data Uniformity

This database structure maintains data uniformity even when queries are made across different applications or database copies, ensuring all instances have the same data at all times, even when dealing with large data volumes.


Relational databases apply integrity constraints to ensure data is accurate and consistent, thus avoiding inconsistent intermediate results that could leave the database in an invalid state.

Query Capability

The use of SQL (Structured Query Language) for data queries and manipulations in this type of database allows for efficient data retrieval and manipulation.


Atomicity refers to the property of executing a transaction as an indivisible, logical unit of work, ensuring all operations within a transaction are completed successfully or completely undone if any error occurs.

Here, the concepts of "rollback," or the reversal of all operations carried out up to that point, and "commit," or the confirmation of the transaction, come into play, making the changes permanent.


Relational databases offer robust security mechanisms to protect stored data, facilitating access levels and permissions to ensure only authorized users can access the data.

Why Quality Data in Your Relational Database is Essential for Automated Testing

As seen throughout the text, relational databases have become the quality standard for storing and managing coherent, secure, and rule-based structured information.

Having a relational database is indispensable if your application needs it; otherwise, the application or software wouldn't start.

Thus, data structures (or row sets) appropriate for testing become an essential element. For example, if a test to create a new bank account for an existing customer is to be launched, that "existing customer" must be present in the database.

As systems become more complex (i.e., as information needs to be present across multiple databases of multiple systems), having coherent and quality data in the various relational databases that make up the system becomes even more important. Following the example, this will allow the creation of that customer through the main application (a CRM, for example), synchronizing it with the rest of the systems.

The reality is that without adequate data, accessing the benefits of automated testing is not possible.

Among the needs for successful automated test data execution are at least the following three points:

  1. Availability of input data relevant to the test case in question and appearing in the correct state with a consistent data profile across all applications in the test environment
  2. Synchronization and availability of context data across all involved applications
  3. Implementation of the comparison of execution results with the expected results in the databases of different applications after completing the automated execution

Having a quality relational database is one of the winning strategies for quality automated testing execution.

An example of a relational database can explain simply what this implies. The imagined table can be the list of patients in a hospital. Thus, it has several rows and columns: each row corresponds to a customer, with their identification number, while the columns describe parameters (name, age, address, phone number, date of the last consultation, etc.). It is precisely the use of this identification number that will allow relating the data of a patient in this table with others.

It is in this context that platforms like icaria TDM gain value, capable of providing the data testers and automated tests need when they need it and as often as necessary; also protecting sensitive information.

Discover how the platform can assist you in managing a relational database in the context of software testing, saving resources and reducing costs always in accordance with current legality. Contact our team and request a demo to discover firsthand the potential of icaria TDM.