"consistency" in CAP vs ACID

 

🧱 1. ACID Consistency (Database Transactions)

Context: ACID is a set of properties that ensure reliable processing of database transactions (especially in traditional relational databases).

• ACID stands for:

  • Atomicity – All or nothing.

  • Consistency – Maintains database rules.

  • Isolation – Transactions don’t interfere.

  • Durability – Once committed, it stays.

✅ What "Consistency" Means in ACID:

The database must start and end in a valid state, following all integrity rules (e.g., constraints, triggers, foreign keys, etc.).

For example:

• If you transfer $100 from Account A to B, the total balance should remain the same.

• If a transaction leaves the database in an invalid state (like negative balance when it’s not allowed), it violates consistency.

🔁 If any step fails, the transaction is rolled back, preserving data integrity.

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🌐 2. CAP Consistency (Distributed Systems)

Context: CAP theorem (also called Brewer’s theorem) applies to distributed systems and says you can only guarantee two out of the three:

• Consistency

• Availability

• Partition Tolerance

✅ What "Consistency" Means in CAP:

All nodes see the same data at the same time – like a single, up-to-date view of the data, regardless of which node you query.

Imagine a replicated database:

• If you write a value x = 5 to one node,

• A read from any node immediately after should return x = 5.

This is often called "linearizability" or strong consistency.

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🔍 Key Differences Between ACID and CAP Consistency:

Feature	ACID Consistency	CAP Consistency
📚 Context	Databases / Transactions	Distributed systems / networks
🎯 Goal	Ensure valid data by enforcing rules (e.g., constraints, referential integrity)	Ensure all replicas have the same data at the same time
🧠 Focuses on	Correctness of state before and after transaction	Same view of data across nodes
💥 Violation	Happens when data violates rules after a transaction (e.g., null in a NOT NULL column)	Happens when nodes return different results after a write
🔄 Rollback?	Yes, rollback restores consistency	No rollback; focus is on how to sync nodes or handle divergence

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🧠 Example to Compare:

Imagine a banking app:

ACID Consistency:

• You must not allow transferring money from an account with insufficient balance.

• If this happens, the system rolls back.

CAP Consistency:

• You made a transaction to transfer money.

• You check balance on one server and it shows updated balance.

• Your phone (connected to another replica) still shows the old balance.

• This is a CAP consistency problem, because both replicas are not in sync.

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🚨 Common Confusion:

• ACID consistency is about valid states, often on a single node or database.

• CAP consistency is about same view of data across multiple nodes in a network.