Non-relational databases, often referred to as NoSQL databases, are designed to store and manage data in a way that does not rely on a fixed schema or tabular structure. Instead of organizing data into tables with rows and columns, non-relational databases can store data in various formats, such as key-value pairs, documents, or graphs. This flexibility allows for the handling of unstructured, semi-structured, or structured data.

One of the key advantages of non-relational databases is their ability to adapt quickly to changing requirements. Since they do not require a predefined schema, modifications to the data structure can be made without affecting existing data. This makes them particularly suitable for applications that need to scale rapidly or handle large volumes of diverse data types. Examples of non-relational database engines include MongoDB, Apache Cassandra, and Redis ¹².

However, non-relational databases also come with some drawbacks. They typically have lower reliability compared to relational databases, and ensuring data integrity and consistency can be more challenging. Additionally, they often require manual query languages, which may complicate data retrieval ¹³.