kiitos
kiitos
https://github.com/DiceDB/dice/pull/1588
This PR attempted to fix the memory model violation I mentioned in the parent comment, but also added in an extra change that swapped the sync.Mutex to a sync.RWMutex. The PR description claimed 2 benefits: "Eliminates the data race, ensuring thread safety" -- correct! at least to some level; but also "Improves performance by allowing concurrent ExpandID calls, which is likely a common operation" -- which is totally unsubstantiated, and very likely false, as RWMutex is only faster than a regular Mutex under very narrowly-defined load patterns.
In any case, the PR had no kind of test or benchmark to validate either of these claims, so not a great start by the author. But then a maintainer chimed in with a comment that expressed concerns about edge-condition performance details, without any kind of data or evidence, and apparently didn't care about (or know about?) the much more important fixes that the PR made re: data races.
https://github.com/DiceDB/dice/pull/1588#issuecomment-274521...
> I tried changing this, but I did not see any benefit in benchmark numbers.
No apparent understanding of the bugs in this code, nor how changes may or may not fix those bugs, nor really how performance is defined or can be meaningfully evaluated.
Again, hobby project or whatever, all good. But the authors and maintainers of this project are clearly, demonstrably, in over their heads on this one.
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senderista
Haven't looked at the code, but enforcing mutual exclusion between writers but not readers can make sense for a single-writer lock-free algorithm.
ignoramous
> single-writer lock-free algorithm
I understand the need for correct lock-free impls: Given OP's description, simply avoiding read mutexes can't be the way to go about it?
nebulous1
I don't use Go.
If I'm reading this correctly, they are recommending a lock in this situation. However, they are saying the implementations has two options, either raise an error reporting the race (if the implementation is told to do so), or, because the value being read is not larger than a machine word, reply to the read with a correct value from a previous write. If true then it cannot reply with corrupted data.
senderista
Oh, so cycleMap is a non-threadsafe structure? I don't know golang so I didn't realize this.
deazy
Looking at the diceDB code base, I have few questions regarding its design, I'm asking this to understand the project's goals and design rationale. Anyone feel free to help me understand this.
I could be wrong but the primary in-memory storage appears to be a standard Go map with locking. Is this a temporary choice for iterative development, and is there a longer-term plan to adopt a more optimized or custom data structure ?
I find the DiceDB's reactivity mechanism very intriguing, particularly the "re-execution" of the entire watch command (i.e re-running GET.WATCH mykey on key modification), it's an intriguing design choice.
From what I understand is the Eval func executes client side commands this seem to be laying foundation for more complex watch command that can be evaluated before sending notifications to clients.
But I have the following question.
What is the primary motivation behind re-executing the entire command, as opposed to simply notifying clients of a key change (as in Redis Pub/Sub or streams)? Is the intent to simplify client-side logic by handling complex key dependencies on the server?
Given that re-execution seems computationally expensive, especially with multiple watchers or more complex (hypothetical) watch commands, how are potential performance bottlenecks addressed?
How does this "re-execution" approach compare in terms of scalability and consistency to more established methods like server-side logic (e.g., Lua scripts in Redis) or change data capture (CDC) ?
Are there plans to support more complex watch commands beyond GET.WATCH (e.g. JSON.GET.WATCH), and how would re-execution scale in those cases?
I'm curious about the trade-offs considered in choosing this design and how it aligns with the project's overall goals. Any insights into these design decisions would help me understand its use-cases.
Thanks
deazy
I was hoping for a response, but no one bothered. I had noted the following when I made that comment and will just wrap up from my end so this could be used by others for reference later.
I'm skeptical that the re-execution approach can scale for complex queries, the latency and throughput improvements would be offseted by the computational cost and bottlenecks introduced for achieving it via its reactivity mechanism (query subscription), this might not work at scale and serve niche use cases.
There are various ways throughput and latency for kv stores can be improved, so bar is really high here.
The messaging with Dice seems unclear and confusing to describe its purpose/use-cases over alternatives, or how it achieves them, which could just be how it's marketed. But it seems to be a collection of ideas and a WIP project.
I think reducing data fetching complexity and complex key dependencies for end clients could be appealing, and it would be great to have it at the KV store level, but there is no reason this type of reactivity can't be implemented on top of various clients for existing KV stores (like Redis). And basic WATCH with transactions are even offered out of the box in them.
Deno kv seem nice but its vendor locked, also there are many others like dragonfly, valkey etc, redis could still work, even something over sqlite can work, deno has a selfhosted kv on top of sqlite - https://github.com/denoland/denokv
Also with dice its creator had made this talk
https://hasgeek.com/rootconf/2024/sub/how-we-made-dicedb-a-t...
From that and the thread so far it seems, they want to make some super cache by building a realtime multi-threaded kv store, improving latency and reducing its read load via its reactivity mechanism. Solving the problem of cache invalidation.
Not sure how this will be achieved but there is no harm in trying. From what is said and shared, rationale behind this design and its tradeoffs are not clear, code could be fixed/improved but providing clarity on this is essential for adoption.
bdcravens
Is there a single sentence anywhere that describes what it actually is?
DrammBA
I've seen this more and more with software landing pages, they are somehow so deep into developing/marketing that they totally forget to say what the thing actually is or does, that's why you show it to family and friends first to get some fresh eyes before publishing the site.
lucianbr
In a similar vein, lots of software is Mac-only, but omits to say this anywehere. You just get to the downloads page and see that there are only mac packages.
As if nobody ever uses anything else.
threatripper
Why should they care about non-users. Offering our even mentioning choice only creates uncertainty and confusion in potential customers.
johnisgood
Looks like a Redis clone. The benchmarks compare it to Redis.
Description from GitHub:
> DiceDB is an open-source, fast, reactive, in-memory database optimized for modern hardware. Commonly used as a cache, it offers a familiar interface while enabling real-time data updates through query subscriptions. It delivers higher throughput and lower median latencies, making it ideal for modern workloads.
pcthrowaway
Not 100% a Redis clone, but the API appears to be very similar to Redis of 10 years ago, with some additions that Redis doesn't have. See the list of commands: https://dicedb.io/get-started/installation/
johnisgood
"clone" was not the right term, maybe Redis-look-alike, or something along those lines, something that can be compared to Redis, at least.
jlengrand
I picked that up purely because of the logo / website palette / name choice combinations. Interestingly, not sure it's a good thing.
arpitbbhayani
Arpit here.
DiceDB is an in-memory database that is also reactive. So, instead of polling the database for changes, the database pushes the resultset if you subscribe to it.
We have a similar set of commands as Redis, but are not Redis-compliant.
nebulous1
Would "key-value" not have a place in the description?
This application may be very capable, but I agree with the person saying that its use-case isn't clear on the home page, you have to go deeper into the docs. "Smarter than a database" also seems kind of debatable.
remram
This is a lot clearer than any information I found anywhere else. There wasn't any room on your website, README, or docs for this summary?
bdcravens
This is a common enough pattern that it should have a name, where the submitted link isn't clear, but a single comment on HN is.
arpitbbhayani
It is right there on the landing page. But, let me highlight it a bit.
aloknnikhil
In the list of things that DiceDB is at the top, you should add "an in-memory database". Pretty critical thing to leave out right at the top.
pcthrowaway
in-memory key-value store seems much more accurate
ofrzeta
So like RethinkDB? https://rethinkdb.com/
dkh
Not a month goes by where I don’t remember it at least once and realize that I still miss it.
This seems more like Redis though
Apofis
Question, how does DiceDB differ from Redis pub/sub? https://redis.io/docs/latest/develop/interact/pubsub/
lucianbr
No. I had the exact same problem.
Feels arrogant. "Of course you already know what this is, how could you not?"
goodpoint
The video is also advertisement rather than a real thing.
rvnx
A Redis-inspired server in Go
adhamsalama
Can't wait to feel the impact of garbage collection in my fast cache!
arpitbbhayani
We had a similar thought, but it is not as bad as we think.
We have the benchmarks, and we will be sharing the numbers in subsequent releases.
But, there is still a chance that I may come to bite us and limit us to a smaller scale, and we are ready for it.
arpitbbhayani
Nope. it started as Redis clone. We are on a different trajectory now. Chasing different goals.
bob1029
> Chasing different goals.
What are those goals? I was struggling to interpret a meaningful roadmap from the issue & commit history.
remram
Secret goals are no selling point.
bdcravens
Even clicking through to the Github, after reading the "What is DiceDB?", I'm still not very clear. It feels more like marketing than information.
"What is DiceDB? DiceDB is an open-source, fast, reactive, in-memory database optimized for modern hardware. Commonly used as a cache, it offers a familiar interface while enabling real-time data updates through query subscriptions. It delivers higher throughput and lower median latencies, making it ideal for modern workloads."
remram
The docs do, the site is useless.
> DiceDB is an open-source, fast, reactive, in-memory database optimized for modern hardware.
A Redis-like database with a Redis-like interface. No info about drop-in compatibility, I assume no.
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schmookeeg
Using an instrument of chance to name a data store technology is pretty amusing to me.
bufferoverflow
No chance if we live in a deterministic universe.
dkh
This is essentially what all in-memory data stores have always been
Kinda refreshing to see someone own it and run with it
cozzyd
DiceDB sounds like the name of a joke database that returns random results.
BoorishBears
No it doesn't.
graynk
Yes it does.
Seems we're in a stalemate, where do we go from here?
BoorishBears
OP continues ignoring static from the people who jump to shoddy conclusions.
kreddor
It was my first thought as well, before reading the landing page.
BoorishBears
Yeah, and I'm sure someone clicked it thinking it was a DB for EA's Dice Studios.
If you expose something to enough people you'll get some unreasonable takes and interpretations of it. It's important to ignore them.
weekendcode
From the benchmarks on 4vCPU and num_clients=4, the numbers doesn't look much different.
Reactive looks promising, doesn't look much useful in realworld for a cache. For example, a client subscribes for something and the machines goes down, what happens to reactivity?
alexey-salmin
| Metric | DiceDB | Redis |
| -------------------- | -------- | -------- |
| Throughput (ops/sec) | 15655 | 12267 |
| GET p50 (ms) | 0.227327 | 0.270335 |
| GET p90 (ms) | 0.337919 | 0.329727 |
| SET p50 (ms) | 0.230399 | 0.272383 |
| SET p90 (ms) | 0.339967 | 0.331775 |
Something I still fail to understand is where you can actually spend 20ms while answering a GET request in a RAM keyvalue storage (unless you implement it in Java).
I never gained much experience with existing opensource implementations, but when I was building proprietary solutions at my previous workplace, the in-memory response time was measured in tens-hundreds of microseconds. The lower bound of latency is mostly defined by syscalls so using io_uring should in theory result in even better timings, even though I never got to try it in production.
If you read from nvme AND also do the erasure-recovery across 6 nodes (lrc-12-2-2) then yes, you got into tens of milliseconds. But seeing these numbers for a single node RAM DB just doesn't make sense and I'm surprised everyone treats them as normal.
Does anyone has experience with low-latency high-throughput opensource keyvalue storages? Any specific implementation to recommend?
davekeck
> Something I still fail to understand is where you can actually spend 20ms
Aren’t these numbers .2 ms, ie 200 microseconds?
ajnin
I had the same reaction as you. And that's for 4 simultaneous clients, too, for a single client you get 3159 ops/s (from https://dicedb.io/benchmarks/). I'm not too familiar with in-memory databases in general but I would have expected figures in the millions on modern hardware. Makes me feel there's some hidden bottleneck somewhere and the benchmarks are not purely measuring the performance of the software.
esafak
They also sounded fishy to me. I'd expect closer to 10x as much throughput with Redis: https://redis.io/docs/latest/operate/oss_and_stack/managemen...
bitlad
I think it is fishy based on this - https://dzone.com/articles/performance-and-scalability-analy...
Kerbonut
Looks like your units are in ms, so 0.20 ms.
alexey-salmin
oh thank you, it's just me being blind
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OutOfHere
In-memory caches (lacking persistence) shouldn't be called a database. It's not totally incorrect, but it's an abuse of terminology. Why is a Python dictionary not an in-memory key-value database?
ac130kz
Any reason to use this over Valkey, which is now faster than Redis and community driven? Genuinely interested.
hp77
DragonflyDB is also in that race, isn't it?
ac130kz
From what I looked at in the past, they seem better on paper by comparing themselves to a very old version of Redis in a rigged scenario (no clustering or multithreading applied despite Drangonfly getting multithreading enabled), and they are a lot worse in terms of code updates. Maybe that's different today, but I'm more keen on using Valkey.
hp77
Does Redis support multithreading? Doesn't it use a single-threaded event loop, while DragonflyDB basic version is with multithreading enabled and shared-nothing architecture. Also I found this latest comparison between Valkey and DragonflyDB : https://www.dragonflydb.io/blog/dragonfly-vs-valkey-benchmar...
losvedir
I didn't see it in the docs, but I'd want to know the delivery semantics of the pubsub before using this in production. I assume best effort / at most once? Any retries? In what scenarios will the messages be delivered or fail to be delivered?
remram
This seems orders of magnitude slower than Nubmq which was posted yesterday: https://news.ycombinator.com/item?id=43371097
arpitbbhayani
Different tool. I metrics I am optimizing for are different hence wrote a separate utility. May not be the most optimized one. But I am usign this to measure all things DiceDB and will be using this to optimize DiceDB further.
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huntaub
What are some example use cases where having the ability for the database to push updates to an application would be helpful (vs. the traditional polling approach)?
zupa-hu
One example is when you want to display live data on a website. Could be a dashboard, a chat, or really the whole site. Polling is both slower and more resource hungry.
If it is built into your language/framework, you can completely ignore the problem of updating the client, as it happens automatically.
Hope that makes sense.
There are _so many_ bugs in this code.
One example among many:
https://github.com/DiceDB/dice/blob/0e241a9ca253f17b4d364cdf... defines func ExpandID, which reads from cycleMap without locking the package-global mutex; and func NextID, which writes to cycleMap under a lock of the package-global mutex. So writes are synchronized, but only between each other, and not with reads, so concurrent calls to ExpandID and NextID would race.
This is all fine as a hobby project or whatever, but very far from any kind of production-capable system.