The phenomenon of big data has become a defining characteristic of the technological age. Consequently, new challenges arise, including the types of data and the scale of the information available; traditional relational databases frequently prove inadequate in addressing these demands, resulting in the proliferation of NoSQL databases. This research presents a comprehensive review of NoSQL-based systems and their methodologies for managing extensive data. Furthermore, this study examines the primary categories of NoSQL databases, their optimal attributes, and their strategies for addressing the contemporary "5Vs" of Big Data: volume, velocity, variety, value, and veracity. Additionally, the research highlights the opportunities presented by NoSQL technologies in emerging fields, such as the Internet of Things (IoT), artificial intelligence, and machine learning, alongside the associated risks, including trade-offs in consistency, security challenges, and the lack of standardization. By integrating classification, comparison, and analysis, this review offers a unified perspective that can aid researchers and practitioners in the effective selection and implementation of NoSQL solutions within Big Data contexts.