In a distributed database system, which two properties can be guaranteed simultaneously according to the CAP theorem?
Remember, network failures can happen, so the system must handle partitions.
The CAP theorem states that in the presence of a network partition, a distributed system can guarantee either consistency or availability, but not both. So, consistency and partition tolerance can be guaranteed together.
You are designing a distributed key-value store. During a network partition, you want the system to always respond to client requests even if some nodes are unreachable. Which CAP property are you prioritizing?
Think about whether the system responds or waits during partitions.
Prioritizing availability means the system responds to requests even if some nodes are unreachable, possibly sacrificing consistency.
You want to scale a distributed database across multiple data centers worldwide. Network partitions are common. To maintain strong consistency, what is the likely impact on system availability?
Strong consistency requires coordination among nodes.
Strong consistency requires nodes to coordinate, so during partitions some requests may be delayed or rejected, reducing availability.
A social media platform wants to ensure users always see the latest posts but can tolerate some delays during network issues. Which CAP property combination best fits this need?
Latest posts mean strong consistency is important.
To ensure users see the latest posts, consistency is prioritized along with partition tolerance, accepting possible reduced availability during network issues.
A distributed database replicates data across 5 nodes. During a network partition, 2 nodes become unreachable. If the system prioritizes availability over consistency, how many nodes must respond to a read request to maintain availability?
Availability means responding even if some nodes are down.
Prioritizing availability means the system can respond with data from any reachable node, so only one node's response is needed.