SQL, or Structured Query Language, is a type of database that stores data in a structured format, using tables with rows and columns. SQL databases like PostgreSQL are highly reliable, scalable, and well-suited for complex data models that require consistency and integrity.

In contrast, NoSQL databases like MongoDB store data in a non-structured or semi-structured format, using collections of documents or key-value pairs. NoSQL databases are highly flexible, scalable, and well-suited for data models that require high availability and rapid development.

One of the main differences between SQL and NoSQL databases is the way they handle data relationships. SQL databases use a relational model, which means that data is organized into tables with predefined relationships between them. This makes it easy to query data using SQL, but can be limiting in terms of flexibility and scalability.

In contrast, NoSQL databases use a document-based model, which allows for more flexibility in terms of data structure and relationships. This makes it easy to store and query data with complex or changing schemas, but can be more difficult to manage and query compared to SQL.

PostgreSQL is a popular SQL database that is known for its performance, reliability, and robust feature set. It is well-suited for complex data models that require strict consistency and reliability, such as financial or healthcare applications.

On the other hand, MongoDB is a popular NoSQL database that is known for its flexibility, scalability, and ease of use. It is well-suited for data models that require high availability and rapid development, such as e-commerce or social media applications.

In summary, SQL and NoSQL databases each have their own strengths and weaknesses, and the choice of database ultimately depends on the specific needs of your application. PostgreSQL and MongoDB are just two examples of the many databases available in each category, and it's important to do your research and choose the one that best fits your requirements.