CAP theorem in DBMS Theory - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the CAP theorem stand for in distributed systems?

CAP stands for Consistency, Availability, and Partition tolerance. It explains the trade-offs in distributed databases.

beginner

Define Consistency in the context of the CAP theorem.

Consistency means every read receives the most recent write or an error. All nodes see the same data at the same time.

beginner

What is Availability according to the CAP theorem?

Availability means every request receives a response, without guarantee that it contains the latest write.

beginner

Explain Partition tolerance in simple terms.

Partition tolerance means the system keeps working even if network parts can't talk to each other.

intermediate

Why can't a distributed system have all three: Consistency, Availability, and Partition tolerance at the same time?

Because when network failures happen (partition), the system must choose between being consistent or available, but not both.

Which two properties can a distributed system guarantee simultaneously during a network partition?

A Consistency and Partition tolerance

B All three: Consistency, Availability, and Partition tolerance

C Consistency and Availability

D Availability and Partition tolerance

During a partition, a system can choose to be available and partition tolerant but may lose consistency.

What does Availability guarantee in a distributed system?

A Every request gets a response

B All nodes have the latest data

C System never experiences network failures

D Data is always consistent across nodes

Availability means the system responds to every request, even if data might not be the latest.

Partition tolerance means:

A System stops working during network failures

B System continues working despite network splits

C System always returns consistent data

D System is always available

Partition tolerance means the system keeps functioning even if parts of the network can't communicate.

If a system chooses Availability over Consistency during a partition, what might happen?

A Users see outdated or different data

B System stops responding

C Data is always synchronized

D Network partition is fixed automatically

Choosing availability may cause users to see stale or inconsistent data.

Which of these is NOT a property in the CAP theorem?

A Consistency

B Availability

C Performance

D Partition tolerance

Performance is important but not part of the CAP theorem properties.

Explain the CAP theorem and its significance in distributed system design.

Think about what happens when parts of a network can't communicate.

Describe a real-life example where a system might prioritize Availability over Consistency.

Consider apps where users expect quick responses even if data is slightly outdated.

Practice

1. What does the CAP theorem state about distributed systems?

easy

A. A distributed system can only guarantee two out of Consistency, Availability, and Partition tolerance at the same time.

B. A distributed system can guarantee all three: Consistency, Availability, and Partition tolerance simultaneously.

C. CAP theorem applies only to single-node databases.

D. CAP theorem states that Consistency is always more important than Availability.

Solution

1. Step 1: Understand the CAP theorem basics

   The CAP theorem says a distributed system cannot guarantee Consistency, Availability, and Partition tolerance all at once.

2. Step 2: Identify the correct statement

   Only two of these three properties can be guaranteed simultaneously in a distributed system.

3. Final Answer:

   A distributed system can only guarantee two out of Consistency, Availability, and Partition tolerance at the same time. -> Option A

4. Quick Check:

   CAP theorem = Two guarantees only [OK]

Hint: Remember CAP means pick any two out of three [OK]

Common Mistakes:

• Thinking all three guarantees are possible simultaneously
• Confusing CAP theorem with ACID properties
• Assuming CAP applies to single-node systems

2. Which of the following is a correct example of a system prioritizing Availability over Consistency according to CAP theorem?

easy

A. A DNS system that always responds to queries even if some data is outdated.

B. A system that never allows network partitions.

C. A system that stops responding during network partitions to avoid inconsistent data.

D. A banking system that locks accounts during transactions to ensure exact balances.

Solution

1. Step 1: Identify Availability over Consistency example

   Availability means the system always responds, even if data might be stale or inconsistent.

2. Step 2: Match example to definition

   DNS systems prioritize Availability by responding to queries despite possible outdated data during partitions.

3. Final Answer:

   A DNS system that always responds to queries even if some data is outdated. -> Option A

4. Quick Check:

   Availability > Consistency example = DNS [OK]

Hint: Availability means always respond, even if data is stale [OK]

Common Mistakes:

• Confusing locking with Availability
• Thinking systems can avoid network partitions
• Assuming consistency means always available

3. Consider a distributed database that chooses Consistency and Partition tolerance but sacrifices Availability during network failures. What happens when a network partition occurs?

medium

A. The system automatically heals the network partition.

B. The system continues to serve all requests with possibly stale data.

C. The system ignores partitions and may return inconsistent data.

D. The system refuses to respond to some requests to maintain data consistency.

Solution

1. Step 1: Analyze system choice of Consistency and Partition tolerance

   Choosing Consistency and Partition tolerance means the system must maintain data correctness and handle network splits.

2. Step 2: Understand impact on Availability

   To keep Consistency during partitions, the system sacrifices Availability by refusing some requests.

3. Final Answer:

   The system refuses to respond to some requests to maintain data consistency. -> Option D

4. Quick Check:

   Consistency + Partition tolerance = sacrifice Availability [OK]

Hint: Consistency + Partition tolerance means some requests denied [OK]

Common Mistakes:

• Assuming system serves stale data when consistency chosen
• Thinking partitions are automatically fixed
• Confusing availability with consistency guarantees

4. A developer claims their distributed system guarantees Consistency, Availability, and Partition tolerance simultaneously. What is the most likely issue?

medium

A. The system uses eventual consistency correctly.

B. The system is ignoring network partitions or not truly distributed.

C. The system is using a single-node database.

D. The system is using a caching layer to improve performance.

Solution

1. Step 1: Recall CAP theorem limitation

   CAP theorem states all three guarantees cannot be met simultaneously in a distributed system.

2. Step 2: Identify why claim is incorrect

   If a system claims all three, it likely ignores partitions or is not truly distributed.

3. Final Answer:

   The system is ignoring network partitions or not truly distributed. -> Option B

4. Quick Check:

   All three guarantees impossible in distributed system [OK]

Hint: All three guarantees mean system is not truly distributed [OK]

Common Mistakes:

• Believing eventual consistency means full consistency
• Confusing caching with consistency guarantees
• Ignoring network partitions in design

5. You are designing a global e-commerce platform that must remain available during network partitions but can tolerate some temporary inconsistency. According to CAP theorem, which two properties should you prioritize?

hard

A. Consistency and Partition tolerance

B. Consistency and Availability

C. Availability and Partition tolerance

D. Only Availability

Solution

1. Step 1: Understand system requirements

   The platform must remain available during network partitions and can tolerate temporary inconsistency.

2. Step 2: Match requirements to CAP properties

   Availability and Partition tolerance must be prioritized, sacrificing strict Consistency temporarily.

3. Final Answer:

   Availability and Partition tolerance -> Option C

4. Quick Check:

   Available + Partition tolerant = temporary inconsistency allowed [OK]

Hint: Availability + Partition tolerance means accept temporary inconsistency [OK]

Common Mistakes:

• Choosing Consistency when availability is required
• Ignoring partition tolerance in global systems
• Assuming all three properties can be guaranteed