One big tip I should recommend is to increase the default memory size limit to something more realistic for modern hardware (and arguably this should just be increased on the upstream's side as well, instead of making everyone reconfigure shitty defaults). It's very easy to exceed the memcached default key value, since it's just 1mb; the maximum size of memcached as a whole is 64mb, which is similarly very low. Outside of that, it works very well and the lack of persistence is great at making it not do things it's not supposed to do (which is a big problem with Redis' feature creep, the projects mainpage promoting AI drivel alone should point towards that.)
Never felt the need to go back to memcached except when a legacy dependency needed it.
What do you think of the argument made in the article?
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
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".
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)
Does your argument assume you already have a database, so you might as well use it for your cache mechanism?
APCu count=1000 min=0.000290 avg=0.000318 p50=0.000320 p95=0.000331 max=0.000992 ms
Memcached count=1000 min=0.032422 avg=0.039714 p50=0.037211 p95=0.053261 max=0.091343 ms
MariaDB count=1000 min=0.015680 avg=0.019541 p50=0.018485 p95=0.023855 max=0.103867 ms
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.
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.
Yeah I thought so too. Google "memcache slab starvation" if you want the long story
> Dealing with memcached downtime is incredibly easy, because client libraries generally ignore connection exceptions. For instance, a simple get will just return the default value (or none) if the server is down.
This is a terrible idea in the context of things that might use Redis. If you use Redis with some kind of complex state (say, a document if you're working on a Notion clone, for instance), wtf even is a "default value"? In fact, I actually also want to know when the thing is down.
> Clustering memcached is wonderful, because memcached actually has no clustering built-in.
Yeah bro, this is yet another one of the reasons people use Redis: it handles consensus and clustering for you. What even is this article? It's a master class in straw-manning architectural decisions: most people use hammers as hammers, but screwdrivers make great hammers too, especially if you also need to screw stuff in! I mean.. technically true?
Considering how complex and error prone this is, I don’t want it in my stack.
Have you ever used Redis before? I've literally never had to manage clustering or had any issues with it, and I've been using Redis for like 15 years (including for games where state had to live in multiple regions and could change on a 30- or 60-tick basis).
It is more sophisticated than grab memory per item.
This helped be to understand it better - https://vectree.io/c/memcached-internals-slab-allocation-lru...
The article mentions the default value is a null, which would be the cue to run whatever computationally expensive op or query the db or hit the disk etc... that you would normally run if you had no cache to begin with.
> but screwdrivers make great hammers too
I don't know what your screwdrivers look like but that sounds like a rough time.
It works pretty well when you need to hit something with a solid object a couple times.
“Anyways, Redis homepage aside, you deploy it, and off you go - your trusty cache. You hand the connection string to the people who asked for it, and off you go.”
“None of these things are impossible with Redis, it’s just that memcached’s architecture in general more leans towards these directions, which makes it much, much more straightforward from an operations point of view.”