PostgreSQL Tuning for Cloud-Native Java: Connection Pooling vs. Reactive Drivers

Authors

  • Sandeep Reddy Gundla

DOI:

https://doi.org/10.22399/ijcesen.3479

Keywords:

PostgreSQL Tuning , Java Microservices, Connection Pooling, Reactive Programming, Cloud-Native Architecture

Abstract

With the transition of software development practices under the cloud-native principles, database connectivity is the key to developing scalable and high-performance Java applications. As a widely used and powerful open-source relational database, PostgreSQL officially supports well-known synchronization access and a newfangled reactive model. This article compares connection pooling and reactive driver strategies for handling PostgreSQL connections in a cloud-native Java environment. The test rigs described in this discussion are designed to use real experiments with containers, different workloads, and performance monitoring tools. Each model is evaluated based on how it affects core performance metrics, including throughput, latency, resource utilization, and fault tolerance. Using mature libraries like HikariCP, connection pooling is demonstrated to be effective in stable systems with moderate concurrency due to its ease of use and simplicity, which integrates with existing Java tooling. However, reactive drivers based on R2DBC benefit from the best scalability and performance in high-concurrency, event-driven, event-driven systems using non-blocking I/O and asynchronous execution. The article also discusses practical tuning strategies and implementation guidance that match PostgreSQL's process model. In addition, it outlines hybrid or transitional use cases where both models could be used. The findings are ultimately guidance for choosing and configuring the best fitting PostgreSQL connectivity approach for the everyday modern Java applications in today's fast changing cloud native landscapes.

 

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Published

2025-07-16

How to Cite

Reddy Gundla, S. (2025). PostgreSQL Tuning for Cloud-Native Java: Connection Pooling vs. Reactive Drivers. International Journal of Computational and Experimental Science and Engineering, 11(3). https://doi.org/10.22399/ijcesen.3479

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Section

Research Article