What are Different Types of Databases?

Databases have diverse types: RDBMS (structured with SQL), NoSQL (flexible for unstructured data), Hierarchical (tree-like structure), Network (complex data relationships), and OODBMS (suited for complex structures). The choice depends on data management and application needs. Learn about each of the Database types in detail.

Databases are integral to modern computing, storing and organizing vast amounts of data across various applications. Various databases have been developed over the years, each with unique features and advantages to managing this data. From the traditionally hierarchical and network databases to the more modern relational and object-oriented databases, understanding the different types of Databases is crucial for anyone working with data in the digital age.

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This article explains the four main types of databases, their strengths and weaknesses, and the applications they are most suitable for. Let’s understand.

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Table of Content

• What is a Database?
• What is a Relational database?
• What is an Object-oriented Database?
• What is a Hierarchical Database?
• What is a Network Database?
• What is NoSQL Database?

What is Database?

A database is an organized collection of information stored to make it easy to access, manage, and update. It helps in storing large amounts of data and allows quick retrieval when needed, like a digital filing system. Examples include storing customer details, product information, or website data. There are various types of databases such as relational, object-oriented, hierarchal, network and NoSQL database. Let's understand each in detail. 

What is Relational Database?

A relational database is a type of database that organizes data into one or more tables, each consisting of rows and columns. It is structured for efficient storage, retrieval, and manipulation of information.

A relational database's tables are related based on standard fields or keys. For example, in a store's database, the customer table might have a common field with the order table, linking each order to the customer who placed it.

Relational databases use a structured query language (SQL) to access and manipulate data. SQL allows users to insert, update, delete, and retrieve data from the database.

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Relational databases are widely used in applications such as financial systems, inventory management, and customer relationship management because they can efficiently store and retrieve large amounts of data while maintaining data integrity and consistency.

What is an Object-oriented Database?

Object-oriented databases (OODBs) are another type of available database. They are database management systems (DBMS) that store data as objects rather than tables like relational databases. In an OODB, each object is an instance of a class that defines its attributes and behaviour.

The use of objects allows for more complex data structures and relationships that can be easily modelled in a relational database. For example, an object in an OODB can have attributes that are themselves objects, allowing for creating more complex data structures.

In addition, OODBs can support complex relationships between objects, such as inheritance and polymorphism, allowing for more flexible and extensible data models.

However, OODBs are less widely used than relational databases due to their complexity and the need for a standard query language. They are primarily used in specialized applications such as computer-aided design, multimedia, and scientific research.

What is a Hierarchical Database?

A hierarchical database is a database management system (DBMS) in which data is organized in a tree-like structure with a single root, branches, and leaves. In a hierarchical database, each record has a parent-child relationship. Each parent can have multiple children, but each child can have only one parent.

A hierarchical database allows data to be accessed by following a hierarchical path, starting at the root and proceeding downward. This makes hierarchical databases best suited for applications requiring fast and efficient data retrieval with a fixed, predefined structure.

During the early days of computing, hierarchical databases were popular, especially in mainframe environments, for managing large amounts of data in applications such as banking and accounting. Relational databases, which are more flexible and can handle more complex data structures, have replaced mainly hierarchical databases.

What is a Network Database?

A network database is a database management system (DBMS) that stores data in a network-like structure. Using pointers or links, data in a network database is organized as a collection of records. Child records in a network database have multiple parents, unlike records in hierarchical databases, which can only have one parent per child. This allows for more flexible and complex data structures than hierarchical databases.

In a network database, data is accessed through a navigational model. The records are accessed by following the links or pointers between related records. This makes it the best fit for complex data structures and relationships, such as engineering and scientific applications.

Network databases were popular in the 1970s and 1980s but have largely been replaced by relational databases. They are easier to use and have more standardized query languages. However, some specialized applications, such as computer-aided design and engineering, still use network databases.

What is NoSQL Database?

NoSQL database, also known as a “non-relational” database, is a type of database that stores and retrieves data in a way that is different from traditional relational databases. Unlike relational databases, NoSQL databases are not based on tables with strict schemas and relationships between them. Instead, NoSQL databases use various data models, such as document-oriented, key-value, graph-based, or column-oriented, to store and manage data.

Among various types of databases, a NoSQL database is another type that requires high scalability, performance, and flexibility, such as for web applications, mobile apps, or big data analytics. It is also suitable for handling unstructured, semi-structured, or rapidly changing data that cannot be easily modelled in a traditional relational database.

Some popular NoSQL databases include MongoDB, Cassandra, Redis, Amazon DynamoDB, and Apache HBase. Each has its strengths and weaknesses, and choosing the right database depends on the application’s requirements.

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Conclusion

Databases have diverse types tailored for specific data management challenges. RDBMS is for structured data, NoSQL is for flexibility, hierarchical is for hierarchies, network is for complex relationships, and OODBMS is for intricate structures. Careful consideration of the database type optimizes overall performance, enabling successful data-driven decision-making.