SQL databases are structured and use a fixed schema, while NoSQL databases are unstructured and offer more flexibility. The choice depends on the application’s data requirements and scalability needs.

The distinction between SQL and NoSQL databases is fundamental in the context of full stack development, as it impacts data storage, retrieval, and management strategies. SQL (Structured Query Language) databases are relational databases that use a structured schema, meaning that the data is organized in tables with predefined relationships. This structure ensures data integrity and supports complex queries, making SQL databases ideal for applications requiring transactional reliability and structured data, such as financial systems. Common SQL databases include PostgreSQL, MySQL, and SQLite. In contrast, NoSQL (Not Only SQL) databases offer a more flexible approach to data storage. They can be document-based, key-value pairs, column-family, or graph databases, allowing for unstructured and semi-structured data. NoSQL databases are designed for scalability and can handle large volumes of data across distributed systems, making them suitable for applications with rapidly changing data models or those requiring high availability, like social media platforms. The choice between SQL and NoSQL largely depends on the specific needs of the application; SQL is preferred for structured data and complex queries, while NoSQL is better for flexible, scalable solutions.