SQL databases are relational and structured, using predefined schemas, while NoSQL databases are non-relational and schema-less, offering more flexibility in data storage.

The choice between SQL and NoSQL databases significantly impacts application design and functionality. SQL (Structured Query Language) databases are relational databases that utilize a structured schema to define the organization of data. They rely on tables, rows, and columns, allowing for complex queries and data integrity through established relationships between tables. Common SQL databases include PostgreSQL, MySQL, and SQLite. They are particularly well-suited for applications requiring strong consistency and complex transactions. In contrast, NoSQL (Not Only SQL) databases are non-relational and schema-less, offering more flexibility in how data is stored and accessed. They can handle a variety of data formats, including key-value pairs, documents, and wide-column stores. This flexibility makes NoSQL databases like MongoDB and Cassandra ideal for applications with rapidly changing data requirements or those dealing with large volumes of unstructured data. NoSQL databases often excel in scalability and performance, allowing for horizontal scaling to accommodate increased load. However, they may sacrifice some consistency and complex querying capabilities compared to SQL databases. Understanding these differences is crucial for selecting the right database type based on the specific needs and requirements of your application.