How does an in-memory cache work?
How does an in-memory cache work?
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02-Apr-2025
Updated on 07-Apr-2025
Khushi Singh
07-Apr-2025The in-memory cache stores data directly within the main memory RAM instead of storing it on disk-based systems. Fast data retrieval becomes possible through RAM because its access speed beats the speed of disk operations and database queries. The frequent use of in-memory caches happens to speed up applications by reducing delay and data retrieval requests from slower storage systems.
How It Works
Storing Data:
The initial step in an application data request involves checking the in-memory cache system for the data. The system returns data immediately to the requesting application in case the data exists in the storage (cache hit). A normal cache operation follows two steps after the application checks whether data exists in the in-memory cache. First, the application obtains data from the database source or another storage location. Second, it stores the retrieved data in the cache and finally returns the requested information to the user.
Key-Value Store:
The majority of in-memory caches operate by having a key-value system that associates one-of-a-kind keys with data records. For example:
Eviction Policies:
Caches apply eviction policies including First in First Out - FIFO and Least Recently Used - LRU to manage data eviction because they have limited memory capacity.
Expiration (TTL):
Data expires automatically when it reaches its Time To Live setting (TTL) to eliminate outdated information and optimize memory performance.
Popular Tools:
Three primary in-memory caching solutions are Redis and Memcached, together with Python-specific
functools.lru_cacheand the Java-basedConcurrentHashMapwith TTL.Benefits:
The most suitable application for in-memory caching involves storing highly accessed data points along with session details and complex computation outcomes that need costly regeneration.