Philosophy of Everything

A trilogy about Data Consistency and how to workaround the CAP and PACELC theorems: 1. First issues with multi-region and multi-cloud software scalability 2. Solutions to have enough Consistency without sacrificing Availability and Latency 3. Theoretical arguments on the nature of CAP/PACELC problem and why you cannot find a better solution than the above one Dear reader, please leave a message if you exist! ;)  Also, please share this article if you find it interesting. Thank you.

 moved to  https://software.mihvoi.ro/2026/04/2-flow-consistency-read-your-writes.html 2. Consistency, Availability and low Latency in Distributed system (workarounding the CAP/PACELC theorems)   Introduction: " 1. Cache and Data Consistency in Distributed systems (CAP/PACELC/CRDT) "   TL;DR Full strong Consistency in geographically Distributed systems can only be achieved by sacrificing Availability (per CAP theorem) and with prohibitive Latency costs (per PACELC theorem). However, we can still design consistent enough systems that continue to function when one geographical region is down and without paying the inter-region latency most of the time. While eventual Consistency is OK many times, there are still cases when we want a strong read-after-write consistency for certain read-after-write flows. There is an optimum design that assures strong Consistency inside read-after-writes flows . Arguably, this is the highest Consistency level that can be assure...