Comparison between Database Search Algorithms (SQL and no SQL)

Authors

  • Amel Abdyssalam A Alhaag Faculty of Information Technology, University of Az-Zawiya Author

DOI:

https://doi.org/10.65405/bc8atc11

Keywords:

SQL optimization, NoSQL systems, database algorithms, query performance, in-dexing strategies, distributed databases

Abstract

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.

Downloads

Download data is not yet available.

References

1. Angles, R., & Gutierrez, C. (2022). Graph database algorithms: Performance analysis and optimization strategies. ACM Transactions on Database Systems, 47(3), 1-28. https://doi.org/10.1145/3505245

2. Chang, F., Dean, J., Ghemawat, S., Hsieh, W. C., Wallach, D. A., Burrows, M., ... & Gruber, R. E. (2008). Bigtable: A distributed storage system for structured data. ACM Transactions on Computer Systems, 26(2), 1-26. https://doi.org/10.1145/1365815.1365816

3. Chen, L., & Liu, Y. (2023). Distributed join processing in SQL and NoSQL systems: A comparative study. Proceedings of the VLDB Endowment, 16(8), 1987-2000. https://doi.org/10.14778/3594512.3594523

4. Codd, E. F. (1970). A relational model of data for large shared data banks. Communications of the ACM, 13(6), 377-387. https://doi.org/10.1145/362384.362685

5. DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., ... & Vogels, W. (2007). Dynamo: Amazon's highly available key-value store. ACM SIGOPS Operating Systems Review, 41(6), 205-220. https://doi.org/10.1145/1323293.1294281

6. Patterson, D. A., & Kumar, S. (2022). Query execution patterns in modern database systems: A comprehensive analysis. IEEE Transactions on Knowledge and Data Engineering, 34(8), 3742-3755. https://doi.org/10.1109/TKDE.2021.3089456

7. Selinger, P. G., Astrahan, M. M., Chamberlin, D. D., Lorie, R. A., & Price, T. G. (1979). Access path selection in a relational database management system. Proceedings of the 1979 ACM SIGMOD International Conference on Management of Data, 23-34. https://doi.org/10.1145/582095.582099

Thompson, R., Davis, K., & Wilson, J. (2023). MongoDB query execution engine: Performance analysis and optimization techniques. Journal of Database Management, 34(2), 45-68. https://doi.org/10.4018/JDM.2023040103

Downloads

Published

2025-09-30

How to Cite

Comparison between Database Search Algorithms (SQL and no SQL). (2025). Comprehensive Journal of Science, 9(ملحق 36), 1810-1830. https://doi.org/10.65405/bc8atc11

Most read articles by the same author(s)