CAP & PACELC — Detailed

flowchart TB
  subgraph CAP[CAP Theorem - Brewer/Gilbert-Lynch]
    C1[Consistency<br/>linearizability]
    A1[Availability<br/>every request a non-error response]
    P1[Partition tolerance<br/>required in real networks]
  end

  subgraph PACELC[Abadi 2010 - PACELC]
    IfP[If Partition: pick A or C]
    Else[Else no partition: pick L or C]
  end

  subgraph Levels[Consistency Models]
    LIN[Linearizable]
    SS[Sequential]
    CS[Causal]
    RYW[Read-Your-Writes]
    MR[Monotonic Reads]
    EV[Eventual]
  end

  subgraph Examples[Systems]
    SP[Spanner<br/>CP / EC<br/>TrueTime]
    DY[DynamoDB / Cassandra<br/>AP / EL]
    MG[MongoDB majority<br/>CP / EC]
    CR[CockroachDB<br/>CP / EC]
    RD[Redis<br/>CP single-leader, AP cluster]
    RF[Raft / etcd / Consul<br/>CP / EC]
    KF[[Kafka<br/>CP within ISR]]
  end

  subgraph Mechanisms[Mechanisms]
    QR[Quorums R+W>N]
    HH[Hinted Handoff]
    AE[Anti-entropy / Merkle]
    CRDT[CRDTs]
    PAX[Paxos / Raft]
    LCK[Leases / Locks]
  end

  CAP --> PACELC
  PACELC --> Levels
  Examples --- Levels
  Mechanisms --- Examples

    classDef client fill:#dbeafe,stroke:#1e40af,stroke-width:1px,color:#0f172a;
    classDef edge fill:#cffafe,stroke:#0e7490,stroke-width:1px,color:#0f172a;
    classDef service fill:#fef3c7,stroke:#92400e,stroke-width:1px,color:#0f172a;
    classDef datastore fill:#fee2e2,stroke:#991b1b,stroke-width:1px,color:#0f172a;
    classDef cache fill:#fed7aa,stroke:#9a3412,stroke-width:1px,color:#0f172a;
    classDef queue fill:#ede9fe,stroke:#5b21b6,stroke-width:1px,color:#0f172a;
    classDef compute fill:#d1fae5,stroke:#065f46,stroke-width:1px,color:#0f172a;
    classDef storage fill:#e5e7eb,stroke:#374151,stroke-width:1px,color:#0f172a;
    classDef external fill:#fce7f3,stroke:#9d174d,stroke-width:1px,color:#0f172a;
    classDef obs fill:#f3e8ff,stroke:#6b21a8,stroke-width:1px,color:#0f172a;
    class C1,A1,P1,IfP,Else,LIN,SS,CS,RYW,MR,EV,RF,QR,HH,AE,CRDT,PAX,LCK service;
    class SP,DY,MG,CR datastore;
    class RD cache;
    class KF queue;

Key clarifications

• "CA" systems do not exist in WAN — partitions are real.
• "Consistency" in CAP = linearizability (strongest).
• Most "AP" systems pick eventual consistency, often with knobs (Cassandra's ONE/QUORUM/ALL).
• Spanner uses synchronized clocks (TrueTime) to give linearizable cross-region writes with 5–10 ms wait windows.

Choosing

Need	Pick
Money, ledger, secrets	CP / EC (Spanner, CockroachDB, Postgres + Raft)
Shopping cart, session, social	AP / EL (Dynamo, Cassandra)
Coordination (locks, config)	CP / EC (etcd, ZooKeeper, Consul)
Analytics aggregations	EL with eventual is fine

Practical tips

• Pick the weakest consistency you can tolerate per operation, not per system.
• Read-your-writes is often sufficient and cheap (session pinning).
• For cross-region, latency dominates → expect EL most of the time.

Glossary & fundamentals

Concepts referenced in this design. Each row links to its canonical page; the tag column shows whether it is a high-level (HLD) or low-level (LLD) concept.

Tag	Concept	What it is	Page
HLD	Pub/Sub & message brokers	topics, consumer groups, delivery semantics	pub-sub-pattern
HLD	CAP / PACELC	C vs A under partition; L vs C otherwise	cap-pacelc
HLD	Raft / Paxos consensus	replicated state machine via majority quorum	consensus-raft-paxos
HLD	Logical clocks	Lamport, vector clocks, HLC, TrueTime	logical-clocks
HLD	CRDTs	commutative replicated data types	crdts
HLD	Multi-region & DR	RTO / RPO, active-active, failover	multi-region-dr