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Show HN: Walrus – a Kafka alternative written in Rust
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Re: Show HN: Walrus – a Kafka alternative written in Rust
#22I never understood the popularity of Kafka. It's just a queue with persistent storage(ie. not in-memory queu with ram-size limited capacity) after all.
Re: Show HN: Walrus – a Kafka alternative written in Rust
#23[flagged]
Re: Show HN: Walrus – a Kafka alternative written in Rust
#24Walrus isn’t trying to replace Kafka, but it does beat Kafka in a few narrow areas. It’s a lightweight Rust-based distributed log with a fast WAL engine and modern I/O (io_uring), so the operational overhead is much lower than running a full Kafka stack. If you just want a simple, fast log without JVM tuning, controllers, or the entire Kafka ecosystem, Walrus is a lot easier to run. Kafka still wins on ecosystem, connectors, and massive scale, but Walrus is appealing for teams that want the core idea without the complexity. Really impressed by the direction here, great work!!.
Re: Show HN: Walrus – a Kafka alternative written in Rust
#25[dead]
Re: Show HN: Walrus – a Kafka alternative written in Rust
#26For Kafka alternative written in C++ there's Redpanda [1],[2]. Redpanda claim of better performance but benchmarks showed no clear winner [3]. It will be interesting to test them together on the performance benchmarks. I've got the feeling it's not due to programming language implementation of Scala/Java (Kafka), C++ (Redpanda) and Rust (Walrus). It's the very architecture of Kafka itself due to the notorious head of…
Or it’s I/O-bound.
Re: Show HN: Walrus – a Kafka alternative written in Rust
#27We need Rust alternative not written in Rust
Re: Show HN: Walrus – a Kafka alternative written in Rust
#28Earlier quoted context omitted.
Hi, the creator here, I think its a good idea to have S3 backed storage mode, its kinda tricky to do it for the 'active' block which we are currently writing to, but totally doable for historical data. Also about the kafka API, I tried to implement that earlier, I had a sort of `translation` layer for that earlier, but it gets pretty complicated to maintain that because kafka is offset based, while walrus is message…
TBH I don't think anyone can utilise S3 for the active segment, I didn't dig into Warpstream too much, but I vaguely recall they only offloaded to S3 once the segment was rolled.
The Developer Voices interview where Kris Jenkins talks to Ryan Worl is one of the best, and goes into a surprising amount of detail: https://www.youtube.com/watch?v=xgzmxe6cj6A
tl;dr they write to s3 once every 250ms to save costs. IIRC, they contend that when you keep things organized by writing to different files for each topic, it's the Linux disk cache being clever that turns the tangle of disk block arrangement into a clean view per file. They wrote their own version of that, so they can cheaply checkpoint heavily interleaved chunks of data while their in-memory cache provides a clean per-topic view. I think maybe they clean up later async, but my memory fails me.
I don't know how BufStream works.
The thing that really stuck with me from that interview is the 10x cost reduction you can get if you're willing and able to tolerate higher latency and increased complexity and use S3. Apparently they implemented that inside Datadog ("Labrador" I think?), and then did it again with WarpStream.
I highly recommend the whole episode (and the whole podcast, really).
Re: Show HN: Walrus – a Kafka alternative written in Rust
#29I never understood the popularity of Kafka. It's just a queue with persistent storage(ie. not in-memory queu with ram-size limited capacity) after all.
Most of the other ones at the time it was pop and the data was gone. You had to jump thru some hoops to make it work as persistent. Not 'hard' but just more annoying. Kafka has that out of the box. Where kafka starts to come apart is how to set it up. Its configuration is a bit tedious to setup.
Re: Show HN: Walrus – a Kafka alternative written in Rust
#30Earlier quoted context omitted.
TBH I don't think anyone can utilise S3 for the active segment, I didn't dig into Warpstream too much, but I vaguely recall they only offloaded to S3 once the segment was rolled.
The Developer Voices interview where Kris Jenkins talks to Ryan Worl is one of the best, and goes into a surprising amount of detail: https://www.youtube.com/watch?v=xgzmxe6cj6A tl;dr they write to s3 once every 250ms to save costs. IIRC, they contend that when you keep things organized by writing to different files for each topic, it's the Linux disk cache being clever that turns the tangle of disk block arrangement…
s3 charges per 1,000 Update requests, not sure how it's sustainable to do it every 250ms tbh, especially in multi tenant mode where you can have thousands of 'active' blocks being written to