Get to understand the real impact of database replication latency. In this research white paper we are unveiling the influence of latency on distributed database replication and how latency impacts distributed database replication for MySQL & PostgreSQL. Explore performance, availability, and consistency implications of introducing latency, revealing insights into optimizing database systems for global operations. Download now to make informed decisions for your distributed database strategy.

This research delves deep into the realm of database management systems, specifically MySQL and PostgreSQL, to assess how latency impacts critical aspects such as performance, availability, and consistency in the context of distributed database replication. The study focuses on configuring both databases for transactional replication in a master-slave setup. As businesses expand their global presence and rely on cloud providers like AWS, the relevance of distributed databases surges. Distributing databases yields enhanced overall performance, shorter response times, and the ability to distribute read operations across multiple databases. Additionally, it introduces fail-over protection by maintaining multiple copies on different physical systems.

However, the introduction of geographically separated databases also ushers in latency. In this research, we have meticulously crafted an environment that introduces latency as a variable while mitigating other potential drawbacks tied to geographical separation. To gauge the influence of latency on performance, we’ve defined two crucial metrics: first, the read performance on secondary databases, and second, the Time To Replicate (TTR). For evaluating availability, we rely on TTR, while for consistency, we scrutinize log files that meticulously record changes made to the database

The results of our comprehensive study unveil noteworthy insights. Latency, it appears, does not impose any additional negative impact on performance or consistency. However, it does indeed exert a negative effect on availability.

Armed with insights gained from our evaluation, we endeavor to enhance the implementation of BBRv2. We delve into the kernel, adapting its variables, and striving for optimization. Our efforts yield success, marking a step towards aligning BBRv2 more closely with the Prague standard.