I wrote an article breaking down how a crypto-exchange balance system can reach **100k–1M updates/sec** while keeping correctness and consistency.

I also open-sourced a prototype (**AXS**) implementing the architecture:  
[https://github.com/vx416/axs](https://github.com/vx416/axs)

The article covers:

* **What causes performance bottlenecks in high-throughput balance updates?**
* **How to reach 1M+ updates per second** using event-driven & in-memory designs
* **How to design a reliable cache layer without sacrificing durability**
* **How to build a robust event-driven architecture** that behaves like a DB WAL
* **How to scale from 10M to 100M+ users** through partitioning & sharding
* **How to achieve zero-downtime deployments & high availability**
* **How to implement distributed transactions** while reducing microservice integration complexity

Article link: [https://medium.com/@vicxu/designing-a-high-throughput-balance-system-for-exchanges-handling-millions-of-tps-fa647adc5d70?sk=26c7eb3365b46ac18c73b9fb78f65ccb](https://medium.com/@vicxu/designing-a-high-throughput-balance-system-for-exchanges-handling-millions-of-tps-fa647adc5d70?sk=26c7eb3365b46ac18c73b9fb78f65ccb)

Building a Million-TPS Exchange Balance System — Architecture Breakdown + Open-Source Prototype (AXS)