Causal Consistency
A consistency model that preserves cause-and-effect ordering: if operation A causally precedes B, all nodes see A before B. Weaker than linearizability but stronger than eventual consistency.
What is Causal Consistency?
A consistency model that preserves cause-and-effect ordering: if operation A causally precedes B, all nodes see A before B. Weaker than linearizability but stronger than eventual consistency.
Causal Consistency is a advanced concept that sits in the Consistency Models area of system design. Engineers reach for it whenever they need to reason about real-world trade-offs in that space — not just for textbook correctness, but because real production systems at companies like Netflix, Amazon, and Google make these decisions every day.
If you want to go deeper than this definition — with diagrams, code, and a quiz to lock it in — work through the "Causal Consistency" lesson linked below. It walks through the why, the mechanism, the trade-offs, and how the giants actually use it in production.
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Related glossary terms you might want to look up next.
Eventual Consistency
A consistency model where updates propagate asynchronously and all replicas will eventually converge to the same value. Trades immediacy for availability.
Vector Clock
A logical clock that tracks causality across distributed nodes using a vector of counters. Each node increments its own counter and merges vectors on message receipt.
Lamport Timestamp
A simple logical clock where each event increments a counter. If event A causes event B, A's timestamp is always less than B's. The foundation of logical time in distributed systems.