I stopped using memcached a decade a go in favour of Redis and now use valkey.
Never felt the need to go back to memcached except when a legacy dependency needed it.
I stopped using memcached a decade a go in favour of Redis and now use valkey.
Never felt the need to go back to memcached except when a legacy dependency needed it.
OK.
What do you think of the argument made in the article?
I don't want my cache to silently fail.
Clustering redis is not that hard even if you do it manually and I have only had to do it once.
I never use redis persistence and have a max size set with LRU or whatever the application requires.
With memcached I remember having to mess around the LD_LIBRARY path to link whatever python module I was using at the time
> silently fail
Mature ops would be tracking cache hit ratios right?
It sounds like memcached would be really good in a use case where you really just need an optional stateless pure cache with absolutely zero rope to hang yourself on. A use case where "cache hit ratio" is the goal, not "fiddly in-memory data store".
> absolutely zero rope to hang yourself on
Yeah I thought so too. Google "memcache slab starvation" if you want the long story
> Mature ops would be tracking cache hit ratios right?
Sure, and sentry integrates well with redis in python which is what I use primarily with redis.
I don't think memcached is bad, I just think its old and industry has moved to redis because it offers more while covering the previous use case.
Calling redis fiddly is a mischaracterization. For many use cases I have not had to think more than 30s to setup redis.
(also when I say redis I mean Valkey at this point, even if they are starting to diverge)
There's basically zero reason to use redis. Pretty much every rdbms like mariadb, postgres, etc is just as fast. So then why redis? It's basically needless complexity in your system.
Postgres etc are more complex than Redis, are they not?
Does your argument assume you already have a database, so you might as well use it for your cache mechanism?
Modern rdbms databases already have an in-memory cache. For 99% of projects there's no actual difference. The round trip will end up around 12-22 ms in all best possible cases.
If you're getting 12-22ms latency for your cache reads, the network is your bottleneck. If stored locally, you would get many orders of magnitude faster than that.
The network IS your bottleneck. That's exactly what I'm saying.
Don't even start a socket if possible.Now then do a traceroute. Even to my router it costs 0.547 ms but that's only 1 direction. And a cloud space is hosting many servers, many routers, many switches, with lots of moving pieces so you're realistically adding 1.1 ms per subnet hop and in pretty much every data center that's probably 3-5 hops inside the LAN.
Gotcha. Yes, if you have your cache (let alone services) all across different machines, then this is all irrelevant.
The real question, which few ever ask, is whether your app actually needs more than one server. Servers are so insanely large (up to like 400 Cores) and powerful now that you can get meaningful scale on a single box.
If you can colocate the app and cache (and maybe also the db) on the same server, you can get many orders of magnitude better performance, regardless of which cache it is. Redis, memcached etc all can do 100k or more gets per second (dragonflydb etc claim 10x that due to multithreading).
Hell, with RAM being so expensive now and NVME so fast, sqlite is a VERY attractive option for cache. Plenty written about projects adopting it. Rails in particular is a champion of it.
Security. More precisely, the ability to secure access to redis with a password.
Okay but I can do that with any rdbms and I can secure memcached too lol. So what? How is redis better than a fixed length table in MySQL?