Application developers must choose between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases, each offering distinct advantages for data management. SQL databases, known for their robust, structured schema, have been a mainstay for decades and are ideal for applications requiring data normalization and reliability. In contrast, NoSQL databases, which include document stores, graph databases, key-value stores, and wide-column data stores, provide flexibility and scalability, making them suitable for handling large volumes of unstructured data. NoSQL databases have gained traction in recent years, particularly for their speed and ability to manage dynamic data. Multi-model databases, like Cosmos DB and DynamoDB, offer hybrid solutions, combining features of both SQL and NoSQL. Additionally, the emergence of NewSQL databases, such as Snowflake, bridges the gap by incorporating NoSQL features into SQL frameworks to enhance scalability. Ultimately, the choice between SQL and NoSQL depends on specific project requirements and team expertise, with modern architectures allowing for the coexistence of both database types to meet diverse application needs.