Relational database - basics and applications
Relational database - basics and applications
A relational database stores data in table form and establishes relationships between these tables. This facilitates the efficient organization and retrieval of data. In this article, you will learn what a relational database is, how it is structured and what advantages it offers.
The most important facts at a glance
- Relational databases store data in tabular form and use primary and foreign keys to establish relationships between data points, which enables efficient organization and querying.
- The use of SQL as a standardized language facilitates the definition, querying and manipulation of data in relational databases, enabling complex queries and data management.
- The ACID properties (atomicity, consistency, isolation and durability) ensure data integrity and reliability in relational database transactions, even in the event of system errors or failures.
What is a relational database?
A relational database is a system for storing and accessing data that is related to each other. This form of database is based on the relational database model, which was developed by E. F. Codd in the 1970s. The relational model solved the problem of inefficient and difficult to maintain data structures by introducing a standardized method of organizing data into tables.
In a relational database, data is stored in tables consisting of rows and columns. Each row in a table represents a record, while the columns define the attributes of those records. This structure makes it easy to recognize and use relationships between different data points. These relationships are made possible by merging tables, which makes it easier to connect and query the data.
A fundamental feature of relational databases is the use of keys to establish relationships between tables. A primary key is a unique identifier for a row in a table, while a foreign key is an attribute that refers to the primary key of another table. This makes it possible to logically link data points and perform complex queries.
Design and structure of relational databases
The structure of a relational database is based on the organization of data in tables that are structured by a defined database schema. These tables consist of rows and columns, with each row representing a data record and each column representing an attribute of this data record. The database schema defines how the data is organized logically and physically, which enables efficient storage and retrieval of the data.
The structure of relational databases makes it possible to store data in different tables and link them through relationships. These links are created using keys such as primary and foreign keys that refer to common attributes. This not only ensures better organization and structuring of data, but also increased flexibility and efficiency in data retrieval and processing.
Tables and relationships
Tables are at the heart of every relational database. A table consists of columns, also known as attributes, and rows, known as entries or tuples. Each column defines a data type, such as text, number or date, and each row contains the actual data values. This structure allows for a clear and logical organization of data points.
The relationships between tables, also known as relations, are created using primary and foreign keys. A primary key is a unique identifier for each row in a table, while a foreign key is an attribute that refers to the primary key of another table. There are different types of relationships:
- 1:1 relationships connect exactly one data record of a table with a data record of another table.
- 1:n relationships link one data record of a table with many data records of another table.
- n:m relationships link many data records of one table with many data records of another table and often require a third table for administration.
Key concepts
Understanding key concepts is critical to managing relational databases. A primary key is an attribute or combination of attributes that uniquely identifies each row in a table. This key ensures that no two rows have the same value in the primary key, which ensures the integrity of the data.
A foreign key is an attribute in a table that refers to the primary key of another table. This creates a relationship between the tables, which makes it possible to link and query data from several tables. These keys are fundamental to the structure and functionality of relational databases and enable complex data queries and analyses.
Normalization
Normalization is a design technique that aims to reduce data redundancy and improve data integrity in relational databases. By splitting large tables into smaller, linked tables, the data structure is optimized and data management becomes more efficient. This method has several advantages:
- Reducing redundancies and dependencies
- Creating a more consistent and reliable database
- Improvement of data integrity
- Simplification of data changes and updates
- Increasing the efficiency of data queries
By using normalization techniques, databases can be made more effective and efficient.
There are different normal forms of normalization, each of which must meet certain criteria. The first normal form requires all table attributes to be atomic, i.e. to contain only indivisible values. The second normal form requires that all non-key attributes are completely dependent on the primary key. By applying these normal forms, the database structure is further improved and data integrity is strengthened.
An example of normalization could be splitting a customer table into separate tables for customer addresses and orders. This avoids duplicate information and makes the database clearer and easier to manage.
Advantages of relational databases
Relational databases offer numerous advantages that make them a preferred choice for many applications. One of the main advantages is referential integrity, which ensures that each foreign key value also exists as the value of the corresponding primary key. This prevents data inconsistencies and ensures that the relationships between data points are correct.
Another advantage of relational databases is their flexibility. They allow tables and data to be added, updated or deleted without having to change the entire database structure. This makes them particularly adaptable to changing requirements and facilitates the management of large amounts of data.
Relational databases are also known for their ability to manage and analyze large amounts of data. They provide an intuitive representation of data and facilitate access to related data points. This is particularly useful in areas such as finance and commerce, where data integrity and the ability to manage large amounts of data efficiently are crucial. The type of database chosen plays an important role here.
SQL and relational databases
SQL, or Structured Query Language, is the standardized programming language for defining, querying and manipulating data in relational databases. This language was developed specifically for the relational model and enables users to manage data efficiently and perform complex queries. SQL is widely used and well documented, which facilitates its use in various database systems.
SQL plays a central role in the management of relational databases. It allows you to:
- modify
- delete
- add
- Extract data from tables
and provides a declarative method for querying data. This ability to manipulate and query data efficiently makes SQL an indispensable tool in the world of databases.
Structured Query Language (SQL)
SQL was developed specifically for database queries in the relational model and has established itself as the most important language for this task. SQL has been around for over 40 years and is therefore widely used and well documented. The name SQL originated from its predecessor SEQUEL ('Structured English Query Language'), which shows the close connection to the English colloquial language.
One of the strengths of SQL is its ability to perform complex queries by using declarative queries that do not specify how the data should be retrieved. This feature enables platform-independent use in different database systems and makes SQL a flexible and powerful tool for database management.
Important SQL commands
The most important SQL commands include
- SELECT: is used to retrieve data from a database and is one of the most commonly used commands in SQL
- INSERT: used to insert new data into a table
- UPDATE: is used to update existing data in a table
- DELETE: allows data to be deleted from a table
These commands represent all the essential operations for querying and manipulating data.
UPDATE allows existing data in a table to be modified, while DELETE is used to remove data from a table. These commands provide comprehensive control over the data in an SQL database and are crucial for managing and maintaining the database.
Stored procedures
Stored procedures are predefined blocks of code that encapsulate complex operations and provide reusable functions. These procedures can significantly increase the efficiency of database management by centralizing and standardizing frequently used queries and operations.
Another advantage of stored procedures is:
- the reduction of network load
- Improving performance
- saving development time through the reuse of code blocks
- improving the consistency of database operations.
ACID properties and data consistency
The ACID properties (atomicity, consistency, isolation and durability) are critical to ensuring data integrity in relational databases. These properties ensure that transactions are executed correctly and reliably, even in the event of system errors or failures.
Atomicity ensures that a transaction is either fully executed or not executed at all, preventing data loss and incomplete transactions. Consistency guarantees that a transaction adheres to all defined rules and restrictions of the database. Isolation prevents parallel transactions from influencing each other, and durability ensures that data is stored permanently after a transaction has been completed.
Locking and parallelism
Locking mechanisms are crucial to prevent conflicts when accessing data in relational databases at the same time. These mechanisms ensure that multiple users can access the database simultaneously without causing data inconsistencies.
There are two main approaches to managing concurrency in databases: optimistic and pessimistic locking. In pessimistic locking, resources are locked prematurely to avoid conflicts. Optimistic locking, on the other hand, assumes that conflicts are rare and only checks consistency before committing. Deadlocks can also be avoided with suitable locking strategies.
Relational databases vs. NoSQL databases
Relational databases and NoSQL databases have different strengths and areas of application. Relational databases are optimized for structured data and guarantee a high level of data integrity thanks to their strict schema and ACID properties. They are particularly suitable for applications where consistent and accurate data is crucial, such as in finance and retail.
NoSQL databases, on the other hand, offer greater scalability and flexibility for unstructured data and large distributed data volumes. They often do without a fixed table schema, which enables flexible data modeling. NoSQL databases are therefore particularly suitable for big data applications and real-time web applications. One disadvantage, however, can be the lack of support for complex queries. In this context, cloud databases are becoming increasingly important.
Selection of a relational database management system (RDBMS)
The selection of a suitable relational database management system (RDBMS) depends heavily on a company's specific requirements. Factors such as
- the type of data to be managed
- the expected amount of data
- the required scalability
- the security requirements
play a decisive role in this decision.
There are various RDBMSs on the market, each with their own strengths and weaknesses. Examples include Oracle, MySQL, PostgreSQL and Microsoft SQL Server.
Tools such as the no-code platform AppMaster can greatly simplify the process of data modeling and implementation by providing visual tools for creating data models and backend applications.
The future of relational databases
The future of relational databases will be heavily influenced by the integration of artificial intelligence (AI) and machine learning. These technologies enable more efficient operations and improve performance, especially when processing large amounts of data.
By automating routine tasks and optimizing queries, relational databases will become even more powerful and adaptable to the requirements of modern data management.
What are relational databases used for in practice?
In practice, relational databases are used in a variety of applications. They are ideal for managing inventory data, processing e-commerce transactions and managing large amounts of business-critical customer information. Relational databases provide a secure and consistent method of managing data points that are related to each other while ensuring data integrity.
Examples of the use of relational databases include:
- maintaining data consistency in financial applications
- managing customer information in CRM systems
- processing transactions in retail applications
These applications benefit from the structured and rule-based data management that relational databases provide.
Summary
Relational databases play a central role in modern data management. They provide a structured and efficient method of storing and managing data points that are related to each other. Through the use of tables, keys and relationships, they enable flexible and consistent data management. Normalization reduces redundancy and improves data integrity, while SQL, as a standardized database language, provides a powerful method for data retrieval and manipulation.
The future of relational databases will be further optimized through the integration of AI and machine learning, enabling more efficient operations and improved performance. Relational databases will continue to play a critical role in managing large and complex data sets while maintaining their flexibility and reliability.
If you still have questions about this and cannot find them in the FAQ below, please feel free to contact our experts. We can help you at any time, whether it's about relational databases or software, online stores and more.
Frequently asked questions
-
What is a relational database?
A relational database is a system for storing and accessing interrelated data organized in tables. It is based on the relational model.
-
What are the advantages of relational databases?
The advantages of relational databases include flexibility, data integrity and efficient management of large amounts of data. They provide an intuitive representation of data and facilitate access to related data points.
-
What are ACID properties?
ACID properties stand for atomicity, consistency, isolation and durability. They ensure data integrity in relational databases.
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How do relational databases differ from NoSQL databases?
Relational databases are ideal for structured data and high data integrity, while NoSQL databases are better suited for unstructured data and flexible data models. NoSQL databases also offer greater scalability and performance for large, distributed data sets.
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What role does SQL play in relational databases?
SQL plays a central role in relational databases as it is the standardized programming language for defining, querying and manipulating data. It enables data to be changed, deleted, added and extracted.
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