Cacheul

Cacheul is an in-memory caching layer designed to store frequently accessed data to reduce latency and load on backend systems. It sits between an application and its primary data store, and can be deployed as a per-process cache or as a distributed cache cluster. The goal is to improve throughput in read-heavy workloads while keeping data reasonably fresh.

Data in a cacheul is stored as key-value pairs with optional metadata such as time-to-live (TTL) and size limits. Common eviction policies include least-recently-used (LRU), least-frequently-used (LFU), or fixed expiration. Cacheuls support basic atomic operations and may store simple data types, binary blobs, or serialized objects depending on the implementation.

In local deployments, each application instance maintains its own cacheul; in distributed setups, a central cluster coordinates storage and invalidation to improve cross-instance coherence. Cacheuls often provide mechanisms for cache warming, asynchronous invalidation, and integration with application frameworks via adapters or client libraries.

Invalidation and consistency in cacheuls are achieved through TTL expiration, explicit programmatic invalidation, or write-through/write-behind patterns where backend updates also refresh or update the cache. Consistency models range from strict to eventual, with trade-offs between latency, throughput, and data staleness.

Common use cases include caching user sessions, database query results, and rendered page fragments in web apps, as well as caching upstream data for microservices. Proper sizing, monitoring, and cache warm-up strategies are essential to achieve a high hit rate without exhausting memory.

Limitations include potential data staleness, memory pressure, and added architectural complexity. Availability of the underlying data store is still required; a cacheul that becomes unavailable can force the application to fallback to the primary store. Security considerations include access controls and safeguards against cache poisoning.

See also: Caching, In-memory data store, Memcached, Redis.