In my previous blog, I explored how serializability ensures isolation across transactions while linearizability guarantees real-time consistency of single objects. This post builds on that discussion by diving deeper into serializability, essentially exploring how valid serial transaction orders are nothing but a means to achieve concurrency through conflict-free scheduling. We…
How do modern databases and distributed systems ensure correctness while allowing operations to run concurrently? Two foundational guarantees — serializability and linearizability — offer different answers depending on whether you care about logical correctness or real-time visibility. In this post, we’ll explore what they are, how they differ, and why it’…
In the previous post, we saw how distributed systems escape the chaos of unreliable clocks by using logical time to measure causality instead of seconds. But there’s one domain where time keeps sneaking back in i.e., Coordination. And as already explained in Part I of this series, coordination…
In the last post, we saw how physical clocks betray us! They drift, skew, jump, and bend, creating logs where effects appear before causes and refunds happen before payments. So what do we do when time itself can’t be trusted? We stop measuring time, and start measuring causality. Second…
Distributed systems often behave as if time were universal, objective truth as if two machines agreeing on a timestamp meant they also agreed on the order of events. But clocks in computers are not laws of nature! They drift with time, freeze under load, stumble over leap seconds, and lags…