What is caching in system design?

Caching is a technique that stores a copy of data in a temporary storage location, known as a cache, to serve future requests for that data faster. The primary purpose of a cache is to reduce latency for data access and decrease the load on backend systems.

What are common caching strategies?

Common caching strategies include Cache-Aside (Lazy Loading), Write-Through, Write-Back (Write-Behind), and Read-Through. The choice of strategy depends on the data access patterns, consistency requirements, and the trade-offs between performance and complexity.

System Design Interview

Caching Strategies

Dive deep into caching, a critical component of scalable systems. Learn about different caching patterns, eviction policies, and when to use tools like Redis or Memcached.

Example: LRU Cache in Python

An implementation of a Least Recently Used (LRU) Cache. This is a common interview question and a fundamental caching eviction policy.


                                import collections
                                
                                class LRUCache:
                                    def __init__(self, capacity: int):
                                        self.cache = collections.OrderedDict()
                                        self.capacity = capacity
                                
                                    def get(self, key: int) -> int:
                                        if key not in self.cache:
                                            return -1
                                        self.cache.move_to_end(key)
                                        return self.cache[key]
                                
                                    def put(self, key: int, value: int) -> None:
                                        if key in self.cache:
                                            self.cache.move_to_end(key)
                                        self.cache[key] = value
                                        if len(self.cache) > self.capacity:
                                            self.cache.popitem(last = False)

Our AI Coach can help you explore other eviction policies like LFU (Least Frequently Used) or FIFO (First-In, First-Out) and discuss the trade-offs of each in a system design context.