Databases: Simply explained

What is a Database?

A database is a structured collection of data that is stored and managed in a computer system. It serves to efficiently organize, store, and retrieve information. Databases can consist of one or more interconnected tables, each containing different data records. 

Types of Databases

There are several types of databases, or database models, which differ in their logical structure. The following section discusses the characteristics and possible applications of hierarchical, object-oriented, document-oriented, relational, and non-relational databases.

Hierarchical Databases

Hierarchical databases organize data in a tree structure, with each level having parent and child records. One advantage of this database model is efficient navigation, as data can be quickly navigated and retrieved. This structure is well suited for applications such as file systems, enterprise management systems, and network topologies, which have strict hierarchical relationships between data.

Object-oriented Databases

Object-oriented databases store data in the form of so-called objects, which can contain both attributes and methods. Attributes are properties of objects, while methods describe the behavior/algorithms of objects. This logic is similar to that of object-oriented programming. By using objects, data can be organized in a modular way and complex relationships can be mapped. Object-oriented databases are particularly suitable for complex data models and applications that require a high degree of flexibility. One example of this is multimedia applications, which can be managed efficiently thanks to different types of data such as images, videos, and audio. CAD software can also be managed with object-oriented databases to store complex 3D models and their relationships. 

Document-oriented Databases

Document-oriented databases store and organize data in the form of documents and can contain structured or unstructured data, enabling flexible data modeling without a fixed schema. Document-oriented databases are usually stored in JSON or XML format. This type of database is highly scalable and can therefore process large amounts of data efficiently. Document-oriented databases are well suited for content management systems to store and manage text, images, and videos, for example. This type is also suitable for web applications and big data analytics, as it can efficiently process unstructured or semi-structured data without data modeling. 

Relational Databases

Relational databases use tables composed of data in rows and columns. The data records are organized in the respective rows and the properties in the respective columns. They use complex query languages such as SQL to manipulate and query data. Relational databases support complex relationships between tables, which are defined by primary and foreign keys. They typically offer transaction support with the four ACID properties (atomicity, consistency, isolation, durability) to ensure data integrity and consistency.

Relational databases are widely used in various industries and applications, such as in finance, to store and manage transaction data such as account movements and transaction histories. They are used on e-commerce platforms to manage product data, orders, customer information, and transactions. 

Non-relational Databases 

Non-relational databases, also known as NoSQL databases, use different approaches to data organization that are not based on the relational model. They offer flexibility and high performance for different types of data, such as structured, unstructured, or semi-structured data. They are highly scalable and can easily run on distributed systems to process large amounts of data.

Non-relational databases are often used in big data applications because they can efficiently process unstructured or semi-structured data without requiring complex data modeling. Other areas of application include cloud computing and real-time analytics for processing and analyzing data streams in real time, such as in the advertising industry or the Internet of Things (IoT).

How does a Database work? 

A database consists of various components that work together to store, manage, and retrieve data. The main components of a database include the database management system, the database model, the actual data, the query language, security mechanisms, and indexes. 

The database management system (DBMS) is the central software that manages the database. It provides interfaces for users and applications to access, store, update, and query the data.

The database model defines the structure of the database, including how data is organized and linked together. The various database models were briefly explained in the previous paragraph. The chosen model influences the possibilities for data modeling and querying. 

The data/information is the core of every database. While the data in a relational database is organized in tables, it is stored in the form of documents in document-oriented databases, for example. The structure of the data can differ depending on the chosen database model.

The same applies to the query language. The query language enables users and applications to retrieve, manipulate, and analyze data. SQL is the common query language for relational databases. Other database models may use specific query languages tailored to their structure and functionality.

Security mechanisms serve to protect data from unauthorized access, loss, or damage. These include authentication, authorization, encryption, and monitoring functions that ensure that only authorized users can access and manipulate the data.

Indexes are special structures used to speed up access to data. They contain sorted references to records based on specific attributes, which improves the efficiency of search and query operations. Indexes are used to optimize the performance of database queries, especially with large amounts of data.

The functioning of a database involves various processes, including data manipulation, data retrieval, transaction management, and ensuring data integrity. Data manipulation refers to the insertion of new records, the updating of existing records, and the deletion of records. 

Popular Database Management Systems for Companies

The DBMS monitors and coordinates the processes of a database to ensure efficient and reliable database usage. It also manages the resources of the database, including storage space, physical data access, connection pools, and query processing, to achieve optimal performance and maintain data integrity.

Common database management systems are: 

MongoDB

MongoDB is a document-oriented NoSQL database that offers flexibility, scalability, and high performance. It uses a flexible data model based on BSON (Binary JSON) that enables natural data representation. MongoDB offers horizontal scalability and a wide range of features for data analysis and processing. It is well suited for big data analytics, content management systems, and real-time applications. 

Advantages:

• Scalability
• Flexible data model
• Performance with large amounts of data

Disadvantages:

• Performance losses due to consistency model
• Complexity

DynamoDB

DynamoDB is a fully managed NoSQL database service from Amazon Web Services (AWS) that provides a highly available, scalable, and high-performance database solution. It uses a key-value data model and offers automatic scaling and fast performance for read and write operations. DynamoDB is particularly well suited for applications in the cloud environment.

Advantages:

• Full management
• Automatic scaling
• Fast performance

Disadvantages:

• High licensing costs
• Limited query options

MySQL

MySQL is a relational open-source database known for its reliability, performance, and broad support. It uses the relational data model and offers a comprehensive range of functions for data management and query optimization. MySQL is widely used and is employed in a variety of applications and industries. 

Advantages:

• Reliability
• Broad support and community
• Available free of charge

Disadvantages:

• Limited scalability compared to NoSQL databases
• Complexity in managing large amounts of data

Oracle Database

Oracle Database is a relational database known for its scalability, security, and performance. It offers advanced features for database administration, transaction management, and high availability. Oracle Database is often used in mission-critical applications that have high requirements for data integrity and reliability.

Advantages:

• Scalability
• Security
• Performance

Disadvantages:

• High licensing costs
• Complexity in configuration and management

Microsoft SQL Server

Microsoft SQL Server is a relational database platform from Microsoft that is known for its integration with other Microsoft products and technologies. It offers a wide range of features for data management, business intelligence, and development tools. Microsoft SQL Server is widely used for Windows-based applications and environments. 

Advantages:

• Integration with other Microsoft products
• Extensive business intelligence features
• Powerful development tools

Disadvantages:

• Platform dependency
• High licensing costs

Conclusion

Databases are important tools that enable data to be stored, managed, and retrieved efficiently. The variety of database models, including hierarchical, object-oriented, relational, and non-relational approaches, offers many options for a wide range of applications and requirements. In this context, database management systems play a crucial role by taking over the administration and control of databases. There are many providers of database management systems on the market. Each of these systems has its own characteristics, strengths, and weaknesses, which must be taken into account depending on the specific requirements and objectives of an application. End Of Article