Relational Database Paradigm
This is the most widely used database paradigm and is based on the relational model proposed by Edgar F. Codd in 1970. It uses a structured table format to store data and uses SQL (Structured Query Language) to access and manipulate the data.
Example: MySQL, Postgres
Hierarchical Database Paradigm
This paradigm uses a tree-like structure to store data, where each record has a single parent and one or more child records. It is most commonly used in legacy systems and mainframe applications.
Network Database Paradigm
This paradigm is similar to the hierarchical paradigm, but allows multiple parent-child relationships between records. It is not as widely used as the other paradigms.
Object-Oriented Database Paradigm
This paradigm uses an object-oriented programming model to store and access data. It allows data to be represented as objects, with their own methods and properties.
Document Database Paradigm
This paradigm stores data in a semi-structured format, such as JSON or XML. It is commonly used for storing unstructured or semi-structured data, such as text documents, images and videos.
Example: MongoDB, Firestore, DynomoDB, CouchDB
Column-Family Database Paradigm
This paradigm is also known as a NoSQL (Not only SQL) database and uses a column-based storage model. It is optimized for handling large amounts of data and is commonly used for big data and real-time analytics applications.
Example: Casandra, HBase
Graph Database Paradigm
This paradigm stores data in a graph format, where nodes represent entities and edges represent relationships between them. It is best suited for handling complex relationships and is commonly used in social network and recommendation systems.
Example: Neo4J, DGraph
Thats all for now. I hope you learned something from this blog. Feel free to hit me on Twitter! Also, do check out my repositories on GitHub and don’t hesitate to reach out to me if you would like to work on any of my existing projects or think I would be a good fit in your project.😁