SSDB VS Memcached

I've used SSDB[0] in the past for some really stupid large datasets (20TB)_and it worked really well in production

[0] https://github.com/ideawu/ssdb

> Or wanting to shift the architecture entirely to avoid using memory-bound Redis as a queue with an overflow risk.

I wanted to use SSDB[1] instead of Redis for that reason, but it doesn't support the necessary data structures.

[1] https://github.com/ideawu/ssdb

There is also ssdb https://github.com/ideawu/ssdb

It's 2021 and we have extremely fast key-value lookups using LevelDB/RocksDB, but we're still using RAM-based caching tools [1] [2] [3]. It's time to consider RAM-based caching harmful, and start caching with SSDs for larger datasets and lower costs. For ex: SSDB [4]

[1] https://redis.io/

[2] https://memcached.org/

[3] https://news.ycombinator.com/item?id=29532552

[4] https://github.com/ideawu/ssdb#ssdb-vs-redis

Aside from this particular use-case, which is what most people here are talking about -- I had never heard of the SSDB project, but it interests me because I often use Redis for certain things it's able to do, aside from its in-memory storage, and sometimes the fact that the data is not stored on disk is a bit of a drawback for me, something I have to work around.

> 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.