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 itself. Concurrency control in databases is all about ensuring that transactions running in parallel behave as if they had…
In my last post Bloom Filters: MathMania, we worked through the derivations for optimal number of bits to allocate and the right number of hash functions to use – striking a balance between space, computation, and false positives. But all of that math rested on one simple assumption: the set of…
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’…
Quorum and Consensus appear frequently in distributed-systems literature – especially in discussions around replication, fault tolerance and distributed databases. They often sound like close cousins – both involve replicas "agreeing" on something, both rely on majorities, and both aim to keep a distributed system from drifting apart. Yet, despite these…
Software systems are built on layers of abstractions. Each layer shields developers from the messy realities beneath, allowing them to think in simpler, more reliable terms. One of the most powerful examples of this principle comes from databases called Transactions. Transactions embody the ACID guarantees — Atomicity, Consistency, Isolation, and Durability…