Read: https://jepsen.io/consistency

Operations:

An operation is a transition from state to state. A single variable system might have operations like read and write.

Consistency:

The rules of what operations can run in parallel and how to combine the results of these operations.

History:

A History is a collection of operations. We represent history as an ordered list of invocation and completion operations, splitting each operation into two.

Consistency Models:

A consistency model is a set of histories. We use consistency models to define which histories are “good” or “legal” in a system.

Set of rules that the system will enforce which defines how the system behaves when operating on the state.

Consistency Models:

1. Strict Consistency
2. Sequential Consistency
3. Release Consistency
4. Causal Consistency
5. Eventual Consistency

Strict Consistency: All replicas execute operations in some total order

• That total order preserves the real-time ordering between operations
• If operation A completes before operation B begins, then A is ordered before B in real-time
• If neither A nor B completes before the other begins, then there is no realtime order. But there must be some total order

Sequential Consistency: All replicas execute operations in some total order

• That total order preserves the process ordering between operations
• If process P issues operation A before operation B, then A is ordered before B by the process order (i.e., preserves local ordering)
• If operations A and B are done by different processes then there is no process order between them. But there must be some total order.

Release Consistency:

Causal Consistency: