A key-value store can be designed using various approaches. A common method involves using a hash map for in-memory storage, which offers O(1) average time complexity for lookups, insertions, and deletions. For persistent storage, Log-Structured Merge (LSM) trees are a popular choice. LSM trees optimize for write performance by appending all writes to a commit log and periodically merging sorted data structures (memtables and SSTables) in the background. Consistent hashing is crucial for distributed key-value stores to ensure even data distribution and minimize data movement when nodes are added or removed. When designing, it's also important to consider conflict resolution strategies, such as versioning (e.g., using timestamps or vector clocks), especially in distributed systems where concurrent writes can occur.