Comparison between Database Search Algorithms (SQL and no SQL) (Comprehensive Journal of Science, 2025)
The fast evolution of data management systems gave rise to the emergence of various da-tabase architectures with different search algorithms that are optimized with specific use cases and data patterns. This is a thorough study of the underlying differences between the SQL and the NoSQL database search algorithms, comparing the performance attributes, op-timization strategies, and the applications. By careful study of algorithm techniques, index-ing strategies and query processing patterns, this study offers some insight into the strengths and weakness of each paradigm. The overview includes both conventional rela-tional database management systems (RDBMS) and newer NoSQL, such as document stores, key-value databases, column-family databases and graph databases. The findings show that SQL databases are better than NoSQL systems in complex relational queries and transaction processing, whereas NoSQL systems are better at handling large distributed data with flexi-ble schemas and high throughput demands.
Keywords: SQL optimization, NoSQL systems, database algorithms, query performance, in-dexing strategies, distributed databases