Serverless computing has revolutionized cloud services by abstracting infrastructure management, providing developers with an environment that automatically scales to meet demand. Initially popular in computing, serverless computing has since expanded into the database realm with services such as Amazon Aurora Serverless and Google Cloud Firestore. These databases offer dynamic scaling of storage and compute capacity without the need for developers to manage the underlying infrastructure. Serverless databases have transformed application development by providing a pay-per-use pricing model, which is particularly cost-effective for workloads with unpredictable or fluctuating demand. The serverless model is especially well-suited for microservices, Internet of Things (IoT) applications, and event-driven workloads. With the serverless approach, developers can focus on writing business logic, while the cloud service provider manages the infrastructure. Serverless databases eliminate the need for provisioning, scaling, or patching servers, reducing operational overhead significantly. Furthermore, the model encourages agility and cost efficiency in modern software architectures. This research explores the evolution of serverless computing into the database space, examining its benefits, challenges, and practical applications. By analysing current state-of-the-art serverless databases, we highlight the key features and functionalities of these services and explore their potential for supporting scalable, resilient, and cost-effective applications. Additionally, we evaluate performance characteristics and limitations of serverless databases compared to traditional database management systems.