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DBMS Theoryknowledge~10 mins

CAP theorem in DBMS Theory - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to identify the three properties of the CAP theorem.

DBMS Theory
The CAP theorem states that a distributed system can only guarantee two out of three properties: Consistency, Availability, and [1].
Drag options to blanks, or click blank then click option'
APartition tolerance
BPerformance
CPersistence
DParallelism
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing Partition tolerance with Performance or Persistence.
2fill in blank
medium

Complete the sentence to explain what Consistency means in CAP theorem.

DBMS Theory
Consistency means that every read receives the most recent write or an error, ensuring [1] data across all nodes.
Drag options to blanks, or click blank then click option'
Aeventual
Bstale
Cinconsistent
Duniform
Attempts:
3 left
💡 Hint
Common Mistakes
Choosing 'eventual' or 'stale' which relate to eventual consistency, not strict consistency.
3fill in blank
hard

Fix the error in the statement about Availability in CAP theorem.

DBMS Theory
Availability means every request receives a response, without guarantee that it contains the most recent [1].
Drag options to blanks, or click blank then click option'
Awrite
Bdelete
Cupdate
Dread
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing read with write in this context.
4fill in blank
hard

Fill both blanks to complete the explanation of Partition tolerance.

DBMS Theory
Partition tolerance means the system continues to operate despite [1] between nodes, handling [2] in the network.
Drag options to blanks, or click blank then click option'
Anetwork partitions
Bdata loss
Cfailures
Dslow responses
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing data loss or slow responses with network partitions.
5fill in blank
hard

Fill all three blanks to complete the trade-off explanation in CAP theorem.

DBMS Theory
In the presence of a [1], a distributed system must choose between [2] and [3].
Drag options to blanks, or click blank then click option'
Anetwork partition
Bconsistency
Cavailability
Dperformance
Attempts:
3 left
💡 Hint
Common Mistakes
Choosing performance instead of availability.

Practice

(1/5)
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