Memcached VS node-cache

> Multiple clients racing can't be fixed.

Really? You can't think of a single way for multiple clients to operate on the same data without racing? (Here's a hint if you're still having trouble: https://github.com/memcached/memcached/wiki/Commands#cas.)

Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs.

Oh, thank you! I didn't realize that LRU Maintainer Thread was more than an expiration reaper. When it was first being introduced that was its first responsibility as lazy expiration removal by size eviction meant dead entries wasted capacity. It was all work in progress when I had read about it [1] and talked to dormando, so it got fuzzy. The compat code [2, 3] might have also thrown me off if I only looked at the setting and not the usage. Its a neat variant to all of these ideas.

[1] https://github.com/memcached/memcached/pull/97

stores session state in a session store like Memcached or Redis.

memcached has recently gained the ability to spill to disk: https://github.com/memcached/memcached/wiki/Extstore

we recently implemented this to grow our caches to >50TB

Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers.

In server-side authentication, the session state is stored on the server-side, which can be scaled horizontally across multiple servers using tools like Redis or Memcached.

4. node-cache

One such implementation if you are using nodejs is `node-cache` https://github.com/node-cache/node-cache/blob/master/README.md. However you can probably find an implementation for most any language you are using.

In-process caching may be implemented in a Node.js application through libraries, such as node-cache, memory-cache, api-cache, and others. There is a wide variety of distributed caching solutions, but the most popular ones are Redis and Memcached. They are both in-memory key-value stores and optimal for read-heavy workloads or compute-intensive workloads due to their use of memory rather than the slower on-disk storage mechanisms found in traditional database systems.

If you're looking for a caching library, there are several of them in every language I've ever used. For example, in Node node-cache is very popular (https://github.com/node-cache/node-cache). Every language I've ever worked in has a few of these. They tend to have a pretty similar basic feature set, and they all have at least the same functions that you defined in your project.