Traditional Relational Databases vs. NoSQL Databases: A Review of Differences and Application Scenarios

Since Codd proposed the relational model in 1970, relational databases have been widely adopted in enterprise data management because of their structured model, standardized SQL, and ACID transactions. With the growth of the Internet, cloud computing, and the Internet of Things, data volume, types, and business requirements have become increasingly diverse. Traditional relational databases therefore face new technical requirements in large-scale distributed, high-concurrency, and frequently changing schema scenarios. NoSQL databases have emerged with document, graph, key-value, and column-family models and distributed architectures. Using MongoDB and Neo4j as examples, this paper compares relational and NoSQL databases in technical characteristics and application scenarios, and examines e-commerce, social networks, financial risk control, and enterprise production management. It argues that the two paradigms are complementary rather than substitutive, and that database selection should balance data structure, transactional requirements, access patterns, and scalability. This study provides references for database selection, system architecture design, and data management optimization.