CAP Theorem
In a distributed system, you can only guarantee two of three: Consistency, Availability, and Partition tolerance. You must choose your trade-off.
What is CAP Theorem?
In a distributed system, you can only guarantee two of three: Consistency, Availability, and Partition tolerance. You must choose your trade-off.
CAP Theorem is a advanced concept that sits in the Distributed Systems Core 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 "CAP Theorem" lesson linked below. It walks through the why, the mechanism, the trade-offs, and how the giants actually use it in production.
Learn CAP Theorem in depth
Full interactive lesson with diagrams, code examples, real-world references, and a quiz.
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Related glossary terms you might want to look up next.
Consensus
The process of getting multiple nodes in a distributed system to agree on a single value. The foundation of distributed databases and coordination services.
BASE
An alternative to ACID for distributed systems: Basically Available, Soft state, Eventually consistent. Trades strong consistency for availability.
ACID
Four guarantees for database transactions: Atomicity (all or nothing), Consistency (valid states only), Isolation (no interference), Durability (changes persist).