Performance, Efficiency, and Scalability in Database Management Systems: A Critical and Analytical Review of Specialized Research

• DOI: https://doi.org/10.22533/at.ed.3175925041212

• Palavras-chave: -

• Keywords: Databases; Performance; Efficiency; Scalability; Throughput; Data Management.

• Abstract: Performance, operational efficiency, and scalability are fundamental pillars in contemporary studies of Database Management Systems (DBMSs), particularly in light of the increasing volume, heterogeneity, and velocity of data generation. This research conducts a comprehensive, critical, and analytical review of the specialized literature, examining in an integrated manner DBMS architectures, execution models, and the mechanisms employed to mitigate computational bottlenecks. The analysis delves into partitioning and fragmentation techniques, load-balancing strategies, fine-grained internal parameter optimizations, methods for data ingestion and increasing throughput of large-scale datasets, as well as solutions addressing concurrency, consistency, and transactional integrity. From an analytical perspective, the study goes beyond mapping existing approaches and investigates their behavior under different resource regimes, including memory, CPU, I/O subsystems, and storage architectures, while also considering the effects of deployment in heterogeneous, distributed, and virtualized environments. The works examined were categorized according to their methodological designs, encompassing detailed technical analyses, controlled experiments, benchmarks, and studies focused on the installation, configuration, operation, and maintenance lifecycle of DBMSs. The results of this review provide a critical synthesis of the most consolidated practices, identify recurring limitations in current solutions, and outline promising directions for future research, particularly in the context of efficient data management in diverse and large-scale computational ecosystems.