How deeply does ScyllaDB in Action cover CAP theorem?

Defines the three properties, explains partition trade-offs, and connects them to replica consistency levels and database behavior.

CAP theorem

As explained in ScyllaDB in Action

The CAP theorem states that a distributed data system cannot simultaneously guarantee consistency, availability, and partition tolerance under network partition conditions.

The CAP theorem states that a distributed system cannot guarantee consistency, availability, and network partition tolerance at the same time. Consistency means every request reads the newest write; availability means the system continues serving requests; partition tolerance means it handles disconnected nodes. section 1.2.1

Because distributed systems must tolerate partitions, they choose between consistency and availability during a network split. A consistent system may stop serving requests until replicas receive the required data, while an available system may serve temporarily inconsistent results. section 1.2.1 section 1.4

Consistency levels make the trade-off operational:

QUORUM requires a majority of replicas, balancing correctness and availability. section 1.4
ONE requires a single replica, preserving service through more failures but allowing weaker consistency. section 1.2.1

ScyllaDB is typically classified as AP: during a partition, it prioritizes availability and may converge through eventual consistency. MongoDB is described as CP because writes wait for a primary during a partition. section 1.2.1 section 1.2.5

How ScyllaDB in Action covers it

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Also explained in

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Unit Testing Principles, Practices, and PatternsThe CAP theorem states that a distributed data store cannot simultaneously guarantee consistency, availability, and partition tolerance under network partitioning.
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PostgreSQL Mistakes and How to Avoid ThemThe CAP theorem states that a distributed data system cannot simultaneously guarantee strong consistency, availability, and partition tolerance under network partition.
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Think Distributed SystemsThe CAP theorem is a formal impossibility result stating that, under its specified asynchronous system model, a distributed system cannot guarantee consistency and availability during a network partition.

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Related concepts

uptimeuses · Uptime is the duration or proportion of a specified period during which a system or service is operational and available to provide its intended function.
partition toleranceuses · Partition tolerance is the ability of a distributed system to continue operating despite communication failures between parts of the system.
consistencyhas part · Consistency is the property of related data, behavior, outputs, or states agreeing with one another or conforming to defined rules across relevant instances or operations.
PACELC theoremcontrasts with · The PACELC theorem describes distributed-system tradeoffs: consistency versus availability during a network partition, and consistency versus latency when no partition occurs.
distributed systemuses · A distributed system is a computing system whose components run across multiple networked processes or machines and coordinate through communication.

This explainer was generated by Manning's knowledge graph from the text of ScyllaDB in Action. The section links point to the parts of the book it draws on.