The Impact of NoSQL Databases for Data Management and Analysis in Smart Cities

Abstract: Smart city technologies generate massive amounts of data through IoT devices, transportation systems, healthcare services, surveillance systems, and smart energy platforms. Managing this continuously growing data using conventional SQL systems has become challenging, as they are primarily intended to manage structured data with predefined formats. NoSQL databases provide a modern solution by supporting scalable storage, flexible schema design, distributed computing, and real-time processing. This study explores how NoSQL databases support data management and analytical processes in smart city environments. Different NoSQL models such as document databases, key-value stores, column-family databases, and graph databases are discussed along with their applications in traffic management, healthcare monitoring, smart parking, and energy optimization. The study also compares SQL and NoSQL systems based on scalability, flexibility, and performance. The findings indicate that NoSQL databases provide efficient handling of large-scale and heterogeneous smart city data environments.

Keywords: NoSQL Database, Smart Cities, Big Data, MongoDB, IoT, Real-Time Analytics