PostgreSQL Configuration: Best Practices for Performance and Security (Published)
PostgreSQL configuration significantly impacts database performance and security, yet default settings often prioritize compatibility over optimization. This article presents a comprehensive framework for PostgreSQL configuration, addressing critical aspects including memory allocation, query planning, security hardening, and monitoring. By examining the interdependencies between configuration parameters and their effects on system behavior under various workloads, the article provides a structured approach to database optimization. Memory allocation strategies focus on shared buffers, work memory, and background writer settings to maximize performance while preventing resource contention. Query performance optimization encompasses planner configuration, autovacuum tuning, and parallel execution capabilities to enhance throughput and reduce latency. Security hardening measures include network protection, authentication controls, privilege management, and vulnerability mitigation techniques to safeguard data while maintaining functionality. Comprehensive logging and monitoring strategies enable proactive identification of performance bottlenecks and security threats. Together, these best practices enable organizations to implement secure, high-performance PostgreSQL environments tailored to their specific requirements.
Keywords: Performance monitoring, PostgreSQL, database optimization, memory allocation, security hardening
An Improved Land Mapping and Geographical Information Management System Using Geodatabase (Published)
With data constantly increasing at a tremendous speed, it is crucial to have better knowledge of how information is manipulated and stored for subsequent retrieval and use. The data storage geodatabase strategy is introduced as dependable alternative based on acknowledged relational database concepts, which form foundation of selected database handling system. Simple but well-defined tables composed of distinctive features selected to store and handle spatial data and rule-base for every topographical dataset. In this paper, we developed an improved land mapping and Geographical Information System (GIS) using geodatabase. The study provides an enhanced approach to storing and managing data using a geodatabase, contributing to further research into alternative way of handling big data. Development of a web application that interacts with geodatabase for big data storage without the need of running multiple servers or enterprise class software. Thus this research is useful for those who have need for efficient data storage and management in today’s world of data size and complexities. By storing data within a geodatabase, one can draw from the benefits that come with its data management capabilities to leverage spatial information.
Keywords: Big Data, Geodatabase, NoSQL, ORDBMS, PostgreSQL, RDBMS, SQL