Optimizing PostgreSQL performance : an in-depth analysis of partitioning impact

Abstract

The explosion of data resulting from the exponential growth in the use of digital platforms has generated an urgent demand for efficient solutions to deal with massive volumes of data. Among the new tools that emerged to overcome new challenges, Cassandra and PostgreSQL quickly became popular. However, traditional solutions have become unsatisfactory over time, leading to the search for optimizations that meet the current requirements. Data partitioning emerged as a way to increase the potential for scalability, fault tolerance, and processing speed. This work proposes to explore the partitioning techniques available in PostgreSQL in a cloud environment in order to provide valuable information to optimize data processing performance. A comparison with Cassandra is also provided, duo to its partitioned architecture.