This sort of makes me sad. Redis has strayed from what its original goal/purpose was.
I’ve been using it since it was in beta. Simple, clear, fast.
The company I’m working for now keeps trying to add more and more functionality using Redis, that doesn’t belong in Redis, and then complains about Redis scaling issues.
I may be biased, but I think this announcement is actually a very good sign for Redis, since it shows that the focus is back to the community edition, that is, the source tree you can just download from GitHub (and I believe this is an effect of the license change: it is possible for the company to work on the public tree without competitors to cut&paste the code in SAAS services).
There are few things that are interesting for me about this discussion related to complexity and use cases outside the scope.
1. You can still download Redis and type "make" and it builds without dependencies whatsoever like in the past, and that's it.
2. Then you run it and use just the subset of Redis that you like. The additional features are not imposed to the user, nor they impact the rest of the user experience. This is, actually, a lot like how it used to be when I handled the project: I added Pub/Sub, Lua scripting, geo indexing, streams, all stuff that, at first, people felt like they were out of scope, and yet many shown to be among the best features. Now it is perfectly clear that Pub/Sub belonged to Redis very well, for instance.
3. This release has improvements to the foundations, in terms of latency, for example. This means that even if you just use your small subset, you can benefit from the continued developments. Sometimes systems take the bad path of becoming less efficient over time.
So I understand the sentiment but I still see Redis remaining quite lean, at least for the version 8 that I just downloaded and I am inspecting right now.
What do you think doesn't belong in Redis? I've always viewed Redis as basically "generic datastructures in a database" — as opposed to say, Memcached, which is a very simple in-memory-only key/value store (that has always been much faster than Redis). It's hard for me to point to specific features and say: that doesn't belong in Redis! Because Redis has generally felt (to me) like a grab bag of data structures + algorithms, that are meant to be fairly low-latency but not maximally so, where your dataset has to fit in RAM (but is regularly flushed to disk so you avoid cold start issues).
Sure, there's persistence but it always seemed like an afterthought. It's also unavailable in most hosted Redis services or very expensive when it's available.
There's also HA and clustering, which makes data loss less likely but that might not be good enough.
For the people wondering who would ever use Redis this way, check out Sidekiq! https://sidekiq.org/ "Ephemeral" jobs can be a big trade-off that many Rails teams aren't really aware of until it's too late. Reading the Sidekiq docs doesn't mention this, last time I checked, so I can't really blame people when they go for the "standard"/"best" job system and they are surprised when it gets super expensive to host it.
If your application is happy with an empty Redis, then why run Redis in the first place?
What you say is good in theory, but doesn’t hold in practice.
We use memcached instead of Redis. Cache different layers in different instances so one going down hurts but doesn’t kill. Or at least it didn’t when I was there. They’ve been trying to squeeze cluster sizes and I guarantee that’s no longer sufficient and multiple open circuit breakers happen if more than one cache goes tits up.
Why not just use Memcached, then? Memcached is much better as an ephemeral cache than Redis — Redis is single-threaded. The point of Redis is all of its extra features: if you're limiting yourself to Memcached-style usage, IMO you're using Redis wrong and should just use Memcached.
Generic data structures in memory, grab bag of structures and algorithms... sounds more like a programming language or library than an external tool. C++ STL for example would fit these descriptions perfectly.
Doing everything is a recipe for bloat. In a database, in a distributed cache, in a programming language, in anything.
I think it wouldn't be unfair to compare it to Golang, which has in my opinion a quite unbloated stdlib which allows you do almost anything without external libraries!
This is what I see everywhere. Something is a success and then everybody starts using it wrong. Like Elastic search as database, people use it for searching and then start using it as primary database. Mostly pushed by management BTW not always the software engineer.
That does not match my experience. Engineers learn a new tool, that tool is successful in solving a problem. Whether it is recency bias, incorrect pattern matching, or simply laziness, the tool is used again but with reduced success. Repeat that process a few more times (sometimes in different organizations) and now the tool is way outside the domain, ill-fit to the task at hand, and a huge pain.
That often happens with engineers who pushed that tool getting promoted a few times and building their career on said tool, which is where I have seen this being pushed down, but I think it is important that in most cases are still engineers
> The company I’m working for now keeps trying to add more and more functionality using Redis, that doesn’t belong in Redis, and then complains about Redis scaling issues.
This doesn't sound like a Redis issue, you're just not using the right tool for the job.
No, like yes they pissed a lot of people off and some people did migrate. But a large majority of "enterprise" customers didn't, it's just too much effort for a service you are paying for anyway.
I dunno, MongoDB is as if it's gone, due to a license change in 2018. So asking if redis should be thought of the same as MongoDB is a legitimate question.
This was available for a long time as an extension as part of Redis Stack, but most hosted Redis providers don't make extensions available (I'm assuming due to nuances in Redis's not-quite-open licensing).
If cloud providers which include Redis are now going to include this, it opens up a lot of potential for my use case.
When do you want to store your time series data in Redis and not a database like TimescaleDB or Clickhouse which is optimized for storage on disk and analytics queries?
This sort of makes me sad. Redis has strayed from what its original goal/purpose was.
I’ve been using it since it was in beta. Simple, clear, fast.
The company I’m working for now keeps trying to add more and more functionality using Redis, that doesn’t belong in Redis, and then complains about Redis scaling issues.
I may be biased, but I think this announcement is actually a very good sign for Redis, since it shows that the focus is back to the community edition, that is, the source tree you can just download from GitHub (and I believe this is an effect of the license change: it is possible for the company to work on the public tree without competitors to cut&paste the code in SAAS services).
There are few things that are interesting for me about this discussion related to complexity and use cases outside the scope.
1. You can still download Redis and type "make" and it builds without dependencies whatsoever like in the past, and that's it.
2. Then you run it and use just the subset of Redis that you like. The additional features are not imposed to the user, nor they impact the rest of the user experience. This is, actually, a lot like how it used to be when I handled the project: I added Pub/Sub, Lua scripting, geo indexing, streams, all stuff that, at first, people felt like they were out of scope, and yet many shown to be among the best features. Now it is perfectly clear that Pub/Sub belonged to Redis very well, for instance.
3. This release has improvements to the foundations, in terms of latency, for example. This means that even if you just use your small subset, you can benefit from the continued developments. Sometimes systems take the bad path of becoming less efficient over time.
So I understand the sentiment but I still see Redis remaining quite lean, at least for the version 8 that I just downloaded and I am inspecting right now.
What do you think doesn't belong in Redis? I've always viewed Redis as basically "generic datastructures in a database" — as opposed to say, Memcached, which is a very simple in-memory-only key/value store (that has always been much faster than Redis). It's hard for me to point to specific features and say: that doesn't belong in Redis! Because Redis has generally felt (to me) like a grab bag of data structures + algorithms, that are meant to be fairly low-latency but not maximally so, where your dataset has to fit in RAM (but is regularly flushed to disk so you avoid cold start issues).
If your application can't survive the Redis server being wiped without issues, you're using Redis wrong.
This.
Sure, there's persistence but it always seemed like an afterthought. It's also unavailable in most hosted Redis services or very expensive when it's available.
There's also HA and clustering, which makes data loss less likely but that might not be good enough.
For the people wondering who would ever use Redis this way, check out Sidekiq! https://sidekiq.org/ "Ephemeral" jobs can be a big trade-off that many Rails teams aren't really aware of until it's too late. Reading the Sidekiq docs doesn't mention this, last time I checked, so I can't really blame people when they go for the "standard"/"best" job system and they are surprised when it gets super expensive to host it.
If your application is happy with an empty Redis, then why run Redis in the first place?
What you say is good in theory, but doesn’t hold in practice.
We use memcached instead of Redis. Cache different layers in different instances so one going down hurts but doesn’t kill. Or at least it didn’t when I was there. They’ve been trying to squeeze cluster sizes and I guarantee that’s no longer sufficient and multiple open circuit breakers happen if more than one cache goes tits up.
Why not just use Memcached, then? Memcached is much better as an ephemeral cache than Redis — Redis is single-threaded. The point of Redis is all of its extra features: if you're limiting yourself to Memcached-style usage, IMO you're using Redis wrong and should just use Memcached.
Valkey is not single threaded
Also the datatypes of redis are practical for caching more complex stuff; they are not for using it as a database though
Rarely seen Redis viewed as a database, even if that has been their push for the last few years.
Generic data structures in memory, grab bag of structures and algorithms... sounds more like a programming language or library than an external tool. C++ STL for example would fit these descriptions perfectly.
Doing everything is a recipe for bloat. In a database, in a distributed cache, in a programming language, in anything.
Don't think the argument is "everything", just the things that can be done within the protocol. There's really not much bloat being added considering the "limitations": https://redis.io/docs/latest/develop/reference/protocol-spec
I think it wouldn't be unfair to compare it to Golang, which has in my opinion a quite unbloated stdlib which allows you do almost anything without external libraries!
Yup, agree. Or as I like to call Redis, your "db building kit"
Of course if what you need is a traditional DB then go with a traditional DB
But it offers those data structures and other stuff that fewer competitors have (or has it in a more quirky way)
This is what I see everywhere. Something is a success and then everybody starts using it wrong. Like Elastic search as database, people use it for searching and then start using it as primary database. Mostly pushed by management BTW not always the software engineer.
You'd be surprised how many engineers make these kinda decisions.
That does not match my experience. Engineers learn a new tool, that tool is successful in solving a problem. Whether it is recency bias, incorrect pattern matching, or simply laziness, the tool is used again but with reduced success. Repeat that process a few more times (sometimes in different organizations) and now the tool is way outside the domain, ill-fit to the task at hand, and a huge pain.
That often happens with engineers who pushed that tool getting promoted a few times and building their career on said tool, which is where I have seen this being pushed down, but I think it is important that in most cases are still engineers
> The company I’m working for now keeps trying to add more and more functionality using Redis, that doesn’t belong in Redis, and then complains about Redis scaling issues.
This doesn't sound like a Redis issue, you're just not using the right tool for the job.
I thought people stopped using Redis and moved on to a fork because of licensing issues. Is this true?
We've switched to https://github.com/microsoft/Garnet and been very happy
No, like yes they pissed a lot of people off and some people did migrate. But a large majority of "enterprise" customers didn't, it's just too much effort for a service you are paying for anyway.
I dunno, MongoDB is as if it's gone, due to a license change in 2018. So asking if redis should be thought of the same as MongoDB is a legitimate question.
I just gave valkey-container its 100th star https://github.com/valkey-io/valkey-container
valkey is still dropin compatible now so migration is pretty easy.
plus aws elasticache give you like 30% price cut when you switch to valkey powered engine ; which make it a pretty good incentive.
Only AWS did, and their fork is already lacking several important new features like HEXPIRE.
>`HEXPIRE`
Finally. Hope they implement this soon at Valkey.
The inclusion of Redis timeseries is huge!
This was available for a long time as an extension as part of Redis Stack, but most hosted Redis providers don't make extensions available (I'm assuming due to nuances in Redis's not-quite-open licensing).
If cloud providers which include Redis are now going to include this, it opens up a lot of potential for my use case.
When do you want to store your time series data in Redis and not a database like TimescaleDB or Clickhouse which is optimized for storage on disk and analytics queries?
Likely when it's small enough to keep in RAM and you want to do some sort of on-the fly aggregation/correlation.
Then you can usually just store it in the memory of your application. No need to complicate your stack by running another service.
Isn't this just RocksDB?
Or DuckDB
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