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

Is there a single sentence anywhere that describes what it actually is?

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.

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.

Why should they care about non-users. Offering our even mentioning choice only creates uncertainty and confusion in potential customers.

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.

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/

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.

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.

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?

It is right there on the landing page. But, let me highlight it a bit.

When I ctrl+F the landing page for key and value, I find nothing. Reading it in full, I also come up empty handed. Which part of the landing page implies it's a key value store?

They did not say anything about key/value in their message.

You are absolutely right, my bad.

IMO, replace "More than a Cache. Smarter than a Database." with an actual description.

The saying is cute but does not really convey information the reader is after. And that spot is where you want people to immediately understand what it is.

I changed that :) now the value proposition is right at the top.

Still not clear to me what it is. Only the features it has, without knowing what it is.

Like, imagine a page that only said "SuperTransport -- 0 to 100 in 5 seconds", but it is not clear for the reader if it is a car or a horse or a plane or a parcel service...

... and the reader has to go and guess "hmm, guess due to the acceleration it is probably a car or a motorbike -- wonder of it is for sale or for rent?".

Just put "fast on premise key/value database" in the big font that was there -- if that is what it is. That is purely a guess from me, no idea if that is what it is.

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.

in-memory key-value store seems much more accurate

So like RethinkDB? https://rethinkdb.com/

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

It kinda surprising it was never really continued, but performance was just too bad even if the interface was fantastic.

Why don't you run the open source version?

I did for about a year and the issue is that ORMs have issues and maintainers don't feel the need to make changes.

A Redis-inspired server in Go

Can't wait to feel the impact of garbage collection in my fast cache!

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.

Vertical scaling this language also gets into painful territory quite often, I’ve had to workaround this problem before but never with a thing that felt like this: https://github.com/tailscale/tailscale/blob/main/syncs/shard...

it might help to add 99th percentile numbers to the landing page; would do a better job of showing GC impact.

Nope. it started as Redis clone. We are on a different trajectory now. Chasing different goals.

> Chasing different goals.

What are those goals? I was struggling to interpret a meaningful roadmap from the issue & commit history.

Secret goals are no selling point.

No. I had the exact same problem.

Feels arrogant. "Of course you already know what this is, how could you not?"

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.

Drop in replacement of Redis.

Nope. We are not redis compliant.

seems like a key store, with an ability to watch/subscribe to monitor for the change of values in real time

"A key store, with an ability to watch/subscribe to monitor for the change of values in real time."

Should be the first sentence on their website and repo.

Yes. With DiceDB clients can "WATCH" the output of the commands and upon the change in data, the resultset are streamed to the subscribers.

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?

  | 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 |

UPD Nevermind, I didn't have my eyes open. Sorry for the confusion.

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?

> Something I still fail to understand is where you can actually spend 20ms

Aren’t these numbers .2 ms, ie 200 microseconds?

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...

I think it is fishy based on this - https://dzone.com/articles/performance-and-scalability-analy...

Looks like your units are in ms, so 0.20 ms.

oh thank you, it's just me being blind

Using an instrument of chance to name a data store technology is pretty amusing to me.

No chance if we live in a deterministic universe.

I feel like this needs a ‘Why DiceDB instead of Redis or Valtio’ section prominently on the homepage.

This seems orders of magnitude slower than Nubmq which was posted yesterday: https://news.ycombinator.com/item?id=43371097

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.

ref: https://github.com/DiceDB/membench

Any reason to use this over Valkey, which is now faster than Redis and community driven? Genuinely interested.

DragonflyDB is also in that race, isn't it?

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.

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...

Valkey/Redis support offloading of io processing to special I/O threads.

Their goal is to unload the "main" thread from performing i/o related tasks like socket reading and parsing, so it could only spend its precious time on datastore operations. This creates an asymmetrical architecture with I/O threads scaling to any number of CPUs, but the main thread is the only one that touches the hashtable and its entries. It helps a lot in cases where datastore operations are relatively lightweight, like SET/GET with short string values, but its impact will be insignificant for CPU heavy operations like lua EVALs, sorted sets, lists, MGET/MSET etc.

IO multithreading is still not fully there, there were significant improvements within the first couple of iterations, hopefully, it will improve further. I see that Dragonfly uses iouring, which is not recommended by Google due to security vulnerabilities.

Dragonfly supports both epoll and iouring, and polling engine choice is quite orthogonal to its shared nothing architecture. I do not think that Valkey or Redis will become fully multi-threaded any time soon - as such change will require building something like Dragonfly (or use locks that historically were a big NO for Redis).

(Author of Dragonfly here)

I read Google is limitting the use of io_uring, but I have seen io_uring being used in other Databases, TigerBeetle is another DB which uses io_uring.

I love the "Follow on twitter" link with the old logo and everything, they probably used a template that hasn't been updated recently but I'm choosing to believe it's actually a subtle sign of protest or resistance.

I prefer that over X icon.

Just use Bluesky. It’s the better middle finger.

I like it!

Anyway to persist data in case of reboots?

That's the only thing missing here.

Is Go the only SDK ?

I think performance benchmark you have done for DiceDB is fake.

These are the real numbers - https://dzone.com/articles/performance-and-scalability-analy...

Does not match with your benchmarks.

The benchmark tool is different. I mentioned the same on my benchmark page.

We had to write a small benchmark utility (membench) ourselves because the long-term metrics that we are optimizing need to be evaluated in a different way.

Also, the scripts, utilities, and infra configurations are mentioned. Feel free to run it.

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?

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)?

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.

Interesting -- is that normally done with database updates + polling vs. something purpose-built?

Not sure how many such solutions there are out there so no idea about the norm. I doubt polling is a real option.

You may want to search for realtime databases.

Is this suffering from the same problems like Redis when trying to horizontally scale?

I guess yes.

- proudly open source. cool! - join discord. YAY :(

Who is this for? Can you help me explain why and when I'd want to use this in place of redis/dragonfly

Is Arpit is the system design course guy?

Yes. I do run a sys design course on weekends.

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?

I am not sure if this is satire or not...

nope. We do not support Redis protocol :)

Did you remove support? Cause Google found mentions of it on your website.

Heh. Redis protocol support is still listed on their Linkedin. https://www.google.com/search?q=%22DiceDB%22%20%22supports%2...