Non-relational databases, often referred to as NoSQL databases, are designed to store and manage data in a way that does not require a fixed schema. Unlike relational databases, which organize data into tables with rows and columns, non-relational databases can handle unstructured, semi-structured, or structured data, often represented in formats like key-value pairs or JSON documents.

One of the key advantages of non-relational databases is their flexibility. They allow for rapid adaptation to changing requirements, meaning that modifications to one item do not impact others in the database. This makes them particularly suitable for applications that require scalability and the ability to handle large volumes of data with varying structures. Examples of non-relational database engines include MongoDB, Apache Cassandra, and Redis ¹².

However, non-relational databases also come with some drawbacks, such as lower reliability and challenges in ensuring data integrity and consistency. Additionally, they often require manual query languages, which can complicate data retrieval compared to the standardized SQL used in relational databases ¹³.