A Survey of Data Storage, Retrieval, and Optimization Methods in Modern Databases

Modern database systems require performance optimization techniques and data management approaches to handle the increasing challenges which modern data-driven applications face at larger operational scales. This paper presents a complete review of all current database systems which includes their data storage methods and retrieval techniques and their optimization approaches. The paper examines advanced storage technologies which include relational databases and NoSQL databases and hybrid row-column databases to assess their capabilities for handling both structured data and semi-structured data. The research study investigates NVM-aware storage systems together with data compression technologies which enable better storage efficiency and quicker access performance. The research examines efficient query execution techniques which include indexing systems based on hash and tree ISAM methods and cache-aware optimization techniques that improve execution performance. The paper presents fundamental performance tuning techniques which include query optimization methods and resource allocation strategies and adaptive self-tuning mechanisms that sustain system performance through varying workload conditions. The paper establishes a comprehensive framework which describes how current database technologies impact system scalability, operational performance and fast data processing