Redis 8.8: New array data structure, rate limiter, performance improvements

187 pointsposted 2 days ago
by ksec
(redis.io)

86 Comments

simonw

7 hours ago

> Rate limiting is one of the most common Redis use cases. Traditionally, users implemented rate limiters using server-side Lua scripts combined with client logic. In Redis 8.8, we introduce a window counter rate limiter (by @raffertyyu, together with the Redis team).

I had a look for this and it turns out it's slightly mis-described there - it's not a window counter, it's a "GCRA (Generic Cell Rate Algorithm)" - a leaky bucket algorithm. Code here: https://github.com/redis/redis/blob/unstable/src/gcra.c

The code comments say it was heavily influenced by https://github.com/brandur/redis-cell by Brandur Leach.

It's a neat algorithm (I just learned about it today) - it only needs to store a single integer for each rate-limited key, which is the "Theoretical Arrival Time" when the bucket would next be empty.

Xeoncross

16 minutes ago

I've never liked token buckets (vs sliding window counters) due to the extra work CPU cycles required to "fill" them. It seems like doing an atomic incr on a key based on a `time % 1 minute` or something would be more efficient and then let that key TTL expire X duration later. This results in zero work for rate limiters not in use and only a single push change -> resulting count for ones in use. Nothing but setting the TTL extra is required.

Thanks for the links, I'll checkout the Generic Cell Rate Algorithm!

9dev

10 hours ago

While I love Redis as a versatile tool for external data structures, it's still lacking in two areas IMHO:

One, it would be cool to be able to embed it, similar to sqlite, directly into applications.

Two, the HA story is so much more complicated than it should be. I totally acknowledge that concurrency and distributed computing is hard, but it should not require reading heaps of documentation and understanding two entirely separate multi-node approaches only to figure out there are lots of subtle strings attached that make it impractical for many applications.

flaghacker

9 hours ago

What would be the point of embedding Redis into an application? What's the advantage of using Redis over using the builtin (or third party) data structures of the language the application is developed in?

I'm asking as a non-webdev who never quite got what Redis actually does, but would love to learn.

jchw

7 hours ago

To me the thing I like about Redis is that it gives you a storage engine very suitable for caches; it handles TTLs and memory pressure, as well as built-in serialization with the ability to get better performance by allowing for some data loss. At the same time, many users will be deploying small programs to individual machines. If you could just have Redis be embedded this would make it very operationally simple: no additional daemons and a single file to backup if you want to.

It would also be useful because of the ability to switch modalities. When running a multi node service, you can use Redis to share data between nodes and use Redis pubsub as a communication bus. If you wanted to support a simple single node configuration too, then it wouldn't need to be a special case, it could just go through the same mechanism but with an embedded Redis instance.

It's pretty similar to SQLite: being able to embed more or less a complete storage engine into your app can be very convenient and powerful.

0x457

5 hours ago

Well, if you have a single instance than using language libraries and structures will be better in most cases.

If you use multiple nodes, then you probably want your redis lifecycle not be tied to application lifecycle.

jchw

5 hours ago

I am not aware of an in-process alternative similar to what Redis offers.

WJW

4 hours ago

Well the most basic redis replacement would be just a global hashmap to replace GET and SET, possibly with a background thread to periodically delete expired keys. But obviously that stops working as soon as you get a second node.

The entire value of redis IMO is that is ISN'T inside your normal application, but rather some shared storage that all nodes can use to coordinate and that survives deploys, but that provides more ergonomic data structures than SQL databases. Caches are only one type of such shared data, but things like feature flags, circuit breakers and rate limiters are also super common (and super useful).

s_trumpet

5 hours ago

Mnesia, if you’re using Erlang or Elixir.

jchw

4 hours ago

Unfortunately I have never really used Erlang outside of deploying RabbitMQ. I mostly use Go, Rust, Python, sometimes C/C++.

However, Mnesia seems like it is quite a bit more of a complete distributed database engine than Redis. To me the nicest thing about Redis is just the convenience of what it offers: very fast data structures, serialized, optimized (at least by default) for cases where speed is more important than durability. It is simple on many levels and somewhat constrained in scope. Mnesia seems to be aiming more generally in the distributed database category.

So how do you feel they compare?

wkrp

3 hours ago

Really it would be more like Nebulex/Cachex which provide a really nice caching interface across ETS (what Mnesia is built off of) or other data stores.

freakynit

9 hours ago

Probably because Redis gives you a very well-defined/understood set of rich data structures with built-in behavior like TTL, atomic operations, eviction, and persistence. These things are otherwise usually scattered across native types, helper classes, or entirely separate libraries.

stingraycharles

8 hours ago

It doesn’t seem like the right tool for the job, though. Aren’t your own programming language’s constructs much more well-defined / understood ?

freakynit

8 hours ago

Language's own native data-structures are generally much more capable and vast. 99%+ developers use only a very limited set of those capabilities. This approach packages those most used ones into a nice, consistent DSL.

It's similar in effect to what busybox does to shell utilities, though the motives are different.

atmosx

34 minutes ago

Doesn’t depend on the language? Actually I am thinking of the standard library… Python’s in kinda huge and some are hard (for me) to grasp. Golangs seem pretty simple.

rsalus

5 hours ago

agreed but depends on then language. for instance, the .NET equivalent (MemoryCache) is pretty poor.

simonw

7 hours ago

Redis has some pretty useful primitive that many languages don't:

- HyperLogLog, bloom filter, other probabilistic data structures

- Geospatial operations on stored points and polygons

- Expiring keys, for creating caches

These aren't in most standard libraries, and the Redis implementations tend to be fast, robust and well understood.

0x457

5 hours ago

Can you name a single language that can talk to redis and doesn't have these in a form of a library that integrates with an app better than mystical embedded redis?

Every language you can talk to redis most likely has a library to do that, and it probably works much better with the rest of application than "embedded redis". If it doesn't, it probably has C-FFI and there is "fast, robust and well understood" implementations in C.

simonw

4 hours ago

Sure. But if Redis was embeddable you'd get a robust C-FFI style implementation of those data structures which has been tested a lot more than some random library that has almost no existing users or active maintenance.

(I'm not personally sold on embedded Redis myself, but the question was "Aren’t your own programming language’s constructs much more well-defined / understood?")

zbentley

6 hours ago

A few nice things about doing this in no particular order:

Embedding would make local dev/CI integration testing convenient.

Embedding replicated Redis with each application instance would give you HA benefits while infra-management complexity.

Embedded redis (even via local RPC) is still going to be faster than a lot of languages or frameworks’ built-in data structures. Large array operations in, say, Python are gonna slower than RPCing to Redis (assuming that the data structures are built gradually and not built all at once); to beat Redis you’d have to use numpy or something—-which is definitely preferable, but is extra work if your app already uses Redis for other things.

Just like choosing SQLite over e.g. LMDB or RocksDB, embedded Redis would be a nice future proofing option for small apps during the prototype phase; less would have to be changed to move Redis out of the app than if a different cache or persistence service were chosen.

razighter777

8 hours ago

In practice, mostly scaling sessions and ephemeral data (caching) across multiple intances of a microservice on multiple machines. Seperating the kv store and the application allows upgrading each application while retaining availability and avoiding loss of session data.

mystifyingpoi

9 hours ago

For simple cases, it is probably a total overkill to even consider it, but for something heavier, embedding the database gives you a chance to trivially migrate later to a separate database server.

thefreeman

9 hours ago

Redis is not a database. It’s a key / value store.

rytis

8 hours ago

It kind of is a database:

A key-value database, or key-value store, is a data storage paradigm designed for storing, retrieving, and managing associative arrays, a data structure more commonly known today as a dictionary.

https://en.wikipedia.org/wiki/Key–value_database

theultdev

9 hours ago

that's still a database.

it's not a relational database.

bijowo1676

5 hours ago

you are confusing redis with memcached

noodletheworld

8 hours ago

Why would you embed SQLite?

It’s the same use case with a different api.

A typical (meaningful) example might be communication between threads or actors in a single process, or idempotent tests.

As with SQLite, an external xxx that does this for you is certainly better, etc. but it’s convenient sometimes, to have an application that doesn’t go “now before you run this install Postgres…”.

It’s seldom useful for a web app where you control everything.

adamcharnock

7 hours ago

> One, it would be cool to be able to embed it, similar to sqlite, directly into applications.

I've found myself wanting this on several occasions too. I.e. wanting all my rust backend processes (k8s pods) to have some minimal shared state, without having to spin up a Redis cluster. I've talked to Claude about it a couple of times, and it descends into something like, "you gotta use Raft or CRDTs, and pick 2 out of 3 from CAP". Which honestly seems pretty fair, and indicates to me that I'm dreaming for something magical.

Nonetheless, it is nice to hear someone else asking for this. If this is indeed feasible (even if simple/limited), then I'd be interested to try it.

williamdclt

5 hours ago

I don't know if that'll make you feel any better but yeah, you're indeed asking for the impossible! You need consensus between your nodes that store state _somehow_, either these nodes are Redis and it does that for you, or these nodes are your pods and you need to do consensus yourself (zookeeper might help, but you're definitely in "complicated stuff" territory).

Spinning up an in-memory (no persistence) Redis cluster in your k8s should be easy enough, hopefully?

adamcharnock

2 hours ago

Yeah, fair enough.

And yes, adding a Redis cluster is fine, it is just another moving part to manage. But given that the alternative is made out of unobtainium, I guess that is just the way of it :-)

atmosx

37 minutes ago

> Two, the HA story is so much more complicated than it should be.

Really? I am curious, how would simplify it? It’s a very well defined problem and all the “solutions” are very complicated and with many strings attached. I have managed one or two systems that came in different modalities and you had to pick your poison and had to make sure the other engineering teams understand the trade offs. Some were more successful than others, but “easy” never crossed my mind.

Redis is single threaded and doesn’t concern itself with these things, directly, exactly because Antitez understood the trade offs and made all the right choices.

How would you improve the HA story without sacrificing ease of use and performance on a single thread?

amtamt

10 hours ago

Genuinely interested why we need HA in redis, just not read round robin from multiple non-HA instances? Redis (and memcache) are memory caches and should be treated like that, not like highly consistent distributed session store.

compumike

9 hours ago

> Redis (and memcache) are memory caches and should be treated like that

If you haven't come across Kvrocks yet, it may be worth a look: https://github.com/apache/kvrocks https://kvrocks.apache.org/ . It's a database with a Redis-compatible wire protocol, but the database is stored on disk. This means your working set is not limited by RAM and can be a few orders of magnitude larger! On modern SSDs this is still very fast. I think it improves the durability story as well. But the big win is the orders of magnitude larger database space.

As I've been improving my side project https://totalrealreturns.com/ recently I've ended up using both Redis and Kvrocks together. Redis is great for small global state that needs to be super fast. Kvrocks is great for larger bulk data storage (large precomputed datasets), but also supports a lot of the Redis data structures as well as Lua scripts.

n_e

10 hours ago

Redis is used for plenty of things, not just memory caches.

For example if you use it for session storage, you can't have your application read from a random instance that may or may not contain the session.

tossandthrow

8 hours ago

This case is exactly what he talks about. To get HA just setup more than one redis cache - or rebuild the session if it was lost in the redis cache.

9dev

8 hours ago

It’s not. Imagine a web app that stores your user information in a session store, mapped by your cookie-provided session ID. Your web app searches redis 1 for the session id, but since that key is on redis 2, the lookup fails and the application thinks there is no such session, and rejects the request.

Now you could solve this specific case by sharding by prefix, or by querying all instances, but then you still do not have high availability: if the instance a specific session is on is down, these users cannot authenticate. At that point you’re better off with a single instance.

olavgg

8 hours ago

But that is his point. If you cannot find the session id in redis, you login again. If your Redis server crash, you start a new one and everyone just login again. No data is lost.

9dev

8 hours ago

Sure the data is lost. A session commonly holds arbitrary state, and even if it’s just the login information. This is ridiculous.

tossandthrow

5 hours ago

Obviously these are application decisions.

You, obviously, don't commit important data only to a session that you can loose, if the application does not allow it.

We use redis as infrastructure. To route events and as a cache.

For us redis could go down and we would merely see a degradation of our service with no data loss.

I recommend using redis like that. And then use a database that supports transactions for real data problems.

But we are different. And that's OK.

9dev

4 hours ago

This discussion is a bit weird. We started off from, Redis should have better availability guarantees. Specifically to avoid the degradation of service you described.

But that requires running on multiple instances, which in turn requires to share the data across all replicas.

trumpdong

7 hours ago

If you consider it important, you have to store it in a real database. No buts. If you don't consider it important, sharded redis works fine.

9dev

7 hours ago

Redis is a real database. If I wasn’t convinced it could retain data I hand it, I wouldn’t use it in the first place.

Just because it works for your use case right now doesn’t mean there isn’t room for improvements to support others too.

trumpdong

6 hours ago

> Redis is a real database.

Oh good, then you don't need to do any of the stuff that you suggested to do

tossandthrow

6 hours ago

I don't think you understand what HA means.

The app would look up in both databases. If it exists in any, there would be a session.

Thisnis strictly different from partitioning which I think you are mixing it up with.

Paritioning is for performance not HA

n_e

5 hours ago

> The app would look up in both databases. If it exists in any, there would be a session.

And if you find the session with differing values in both databases, how do you know which one is up-to-date?

You need an algorithm to pick which data is right, such as electing a master instance.

And that brings us back to the original discussion: to manage sessions (unlike caches) in a highly available way, you need to setup HA (or reimplement it, which obviously is a bad idea). You can't read round robin from multiple non-HA instances.

tossandthrow

5 hours ago

Yes, you are pointing out exactly how HA is difficult.

There is a whole slew of downstream things you need to take into consideration.

9dev

2 hours ago

and as you've just confirmed... there is a need for good HA support in Redis. Which was the entire premise of this thread.

9dev

5 hours ago

That’s the precise point I’m making

marklubi

7 hours ago

For the project I've been working on for more than 15 years, we make extensive use of the pub/sub functionality for distributing live data. Pub/sub scales well across the cluster. Publish to one, and it goes out to subscribers on any of the nodes that they've connected to.

Will millions of users, high availability is critical for this functionality.

9dev

10 hours ago

Redis doesn't necessarily have to be used as a cache. Streams, for example, make it a great message queue; but a single-node message queue is a single point of failure and thus not viable for many setups.

acejam

9 hours ago

That's why you run Redis Sentinel in production

9dev

8 hours ago

That you do. Until you realise that there is only a single writer in that scenario, it doesn’t address any sharding concerns, you need to use compatible clients that opt into the sentinel protocol, during failover you’ll see client errors… there’s lots of room for improvement on redis HA.

lukaslalinsky

8 hours ago

With the amount of problems I had using Redis Sentinel, I really wish there was another way. On multiple occasions, with completely different deployments, it got itself into a non-repairable state where the only option was to drop it and setup the replicas manually. I was hoping someone would do a Patroni-like project for Redis, but I've not found it yet. I've moved all persistent data to PostgreSQL and use a number of Valkeys behind Envoy proxy as a cache.

yxhuvud

5 hours ago

Redis have many use cases, and acting as a cache is only one of them. One very common usage is as a backend for background worker jobs. That can need HA.

__s

9 hours ago

Years ago I enabled durability on redis & used it as database for an online card game

echelon

7 hours ago

> it's still lacking in two areas

This is entirely different than what Redis is and tries to solve.

Sqlite is embedded. It's not a distributed SQL. Redis is a distributed data structure store and concurrency primitive. These are worlds apart.

> HA story is so much more complicated than it should be

It is precisely as complicated as it needs to be. You don't want data loss.

If you're in the business of high available fault tolerance, you read the manual and learn how to Redis.

9dev

7 hours ago

What kind of an answer is that? This software is perfect the way it is, you’re just to inept to hold it right?

A high availability protocol should not leak into the client. It should be able to discover other nodes. It should not land in broken states so easily. It should not limit the number of writers. It should not error during failover.

Are these hard problems? Yes. Should we just accept that things are hard because that’s how the gods have given them to us? No.

echelon

4 hours ago

High availability and abstraction complexity are orthogonal.

Redis is a low-level concurrency primitive, and it made certain choices in dealing with CAP.

It might be single-threaded, but it can easily absorb 100,000+ requests per second.

I've built systems that handle billions of dollars of online payments flow, active-active, with six nines of uptime reliability on top of Redis. It does what it says on the tin, and it doesn't need to be everything for everybody. This is a hard domain and you're going to have to deal with different problems and tradeoffs.

If you want something higher level, there are other systems to reach for.

tapoxi

10 hours ago

Where did everyone end up on the Redis/Valkey split? Is there still a reason to use Redis after the license kerfuffle?

jillesvangurp

7 hours ago

We switched to Valkey two years ago. I haven't really looked back. I think both projects have done a lot of nice stuff since the split but it's not really impacting anything I use. The feature set was fine five years ago and I don't think we're using anything in Valkey that wouldn't work in Redis. There are probably a lot of projects that never switched over because they had no real need.

But most of the cloud providers now offer Valkey because of the license changes. Of course, cloud providers not offering Redis was the intention of the license change from the Redis point of view. So mission accomplished for Redis.

But the flip side of course is that if you want to deploy on standard infrastructure rather than self hosting Redis, Valkey is now the easy, low risk path that probably should be the default for most companies that target AWS, Azure, GCP, etc. Same with Elasticsearch vs. Opensearch and a few other products where the community forked because of license changes.

Mentioning Elasticsearch because I know people in both communities and I'm deeply familiar with the stack. A few years on, Opensearch has taken a lot of the momentum from Elasticsearch.

lukaslalinsky

8 hours ago

I've switched to Valkey and I'm not really looking back. I'm much more comfortable with those people maintaining the software.

CamouflagedKiwi

8 hours ago

Valkey, because our cloud provider is hosting it and that's obviously what they prefer.

I feel like we're using about 1% of its features at this point - really just as a fast K/V store - so it would be easy to switch if needed, but I can't see a case where we would.

gadders

8 hours ago

They prefer it because they don't have to pay to use it.

atraac

9 hours ago

We use almost exclusively Valkey now, mostly because we host on AWS and Render, which both use Valkey. It's faster, cheaper and compatible. I'd consider Garnet too but I believe it doesn't support LUA(or didn't at the time we needed it).

stevoski

8 hours ago

We switched to Valkey after the Redis license kerfuffle happened, discovered we were saving money on our AWS bill, and have no motivation to go back to Redis.

So we’ve stayed with Valkey.

olavgg

8 hours ago

We're a self hosted shop, we went with Valkey. Valkey also has support for RDMA, which we already is running in our infrastructure.

kfir

9 hours ago

Went with 100% ValKey, if you are solely on AWS it is a no-brainer

NorwegianDude

7 hours ago

Most people seems to have switched to Valkey, and it's backed by the Linux foundation.

benatkin

2 hours ago

Valkey continues to be the real redis, released under a permissive open source license like redis originally was. The fork of redis known as redis because those that decided to fork it had the trademark at first wasn't under an OSI-certified open source license and now is under a non-permissive OSI-certified open source license.

I'm taking liberties with the concept of forking.

hakube

9 hours ago

We went with DragonFlyDB

ShakataGaNai

5 hours ago

Are we still using Redis? License change, no more Kube operators.

epolanski

10 hours ago

There's also a separate blog post that goes into the details of why existing data structures Redis already supported, which could provide array-like behavior, weren't good enough:

https://redis.io/blog/diving-deep-into-rediss-new-array-data...

focusgroup0

9 hours ago

given his ds4 project, likely collaborated with DeepSeek for this release:

https://github.com/antirez/ds4

JLO64

8 hours ago

Possibly, but the array type code was implemented using GPT/Claude models before DS4 was a thing. I really recommend this write up on how he used LLMs which I think is a more sane/safe way to code with them vs the YOLOing even I'm subject to unfortunately...

https://antirez.com/news/164

zozbot234

7 hours ago

The experimental SSD streaming feature (author's demo @ https://x.com/antirez/status/2062536214675067322 - recently merged into the main branch) is great news for that project, allowing for SOTA inference (DeepSeek V4 Flash and Pro!) on RAM-limited machines. Now we need work on large-ish scale batching in order to recover tok/s under the SSD streaming scenario. It's not helpful when running normally (at least not on Apple Silicon) since thermal/power throttling is the constraint in that case, but SSD streaming is a whole other consideration.

caraphon

8 hours ago

window counter rate limiter!

This is awesome!

And arrays look great too. Lots to play with.

fga_qwrh

7 hours ago

And here we see the reason for the sudden AI enthusiasm of Redis authors: array data structures are used in AI. This was clear weeks ago.

The website looks like openclaw's website.