Relational Databases (RDBMS): Structure: Uses tables to store data, with relationships defined between tables. Examples: PostgreSQL, Oracle, MySQL. Use Case: Suitable for applications where data integrity and complex queries are essential. Strengths: Strong ACID compliance, complex queries with SQL, data integrity. NoSQL Databases: Structure: Non-relational, can store data in formats like key-value pairs, documents, graphs, or wide-column stores. Examples: MongoDB, Cassandra, Redis. Use Case: Ideal for applications requiring high scalability and flexibility, like real-time analytics. Strengths: Horizontal scaling, flexible schemas, performance in distributed systems. Graph Databases: Structure: Uses nodes, edges, and properties to represent and store data. Examples: Neo4j, AgensGraph. Use Case: Perfect for applications involving complex relationships like social networks. Strengths: Efficient querying of relationships, flexible structure. Document-Oriented Databases: Structure: Stores data as JSON-like documents. Examples: MongoDB, CouchDB. Use Case: Best for semi-structured data, such as content management systems. Strengths: Flexible data model, easy to store nested data.