Yes, you get 10x the throughput while maintaining far better tail latency with Scylla over Cassandra.

How is 10ms vs 475 not a major improvement? How is 4 nodes vs 40 not a major improvement? If you're an SRE than how is managing 4 servers with far less tuning and maintenance not a major improvement? Also 99.9% percentile still matters. They're testing with 300k ops/sec which means 300/sec are facing extreme latency spikes that can be enough to fail and/or cause cascading issues through out the application.

There's no metric where Cassandra is better here and you can't tune your way to the same performance in the first place which is the whole point of Scylla. What even is your claim here? Spend more to get less?

2-3x maybe, 10x not likely, unless you compare it to untuned cassandra.

What makes it possible to run cassandra/scylla on nodes with TBs of data density is the TWCS compaction strategy from Jeff Jirsa. He was just a cassandra power user at the time, and I like to think that the invention was possible because of Java.

So, next time you read an ad piece from scylla about replacing 40 mid size boxes running CMS with 4 big boxes, don't forget about TWCS.

It's 4 servers doing the same as 40. That is 10x throughput, and with lower tail latency.

Scylla is far more than a compaction strategy. If it was that simple, than Cassandra would already be able to do it.

It's an objectively faster database in every metric. Datastax's enterprise distribution has more functionality but core Cassandra is now entirely outclassed by Scylla in speed and features.

Again, that's 40 mid size boxes with questionable GC (32G to 48G heap size is the no man land, G1GC target pause time of 500ms of course will result in 500ms P999 latency, etc), versus 4 big boxes, which have more than 4x higher specs. So 10 divides by 4, that's the 2-3x that I mentioned.

The TWCS is just a good example that raw performance is not everything. Performance also comes from things like compaction strategy, data modeling, and access pattern, while users and stakeholders also care about things like easiness to modify, friendly license, and steady stewardship.

How does Scylla relates to Kafka and zookeeper here? I know a bunch of ad-tech companies that built their entire stack around JVM and scala. Those companies need to perform a bid (a whole bunch of logic ) within 100 ms ( including networking), otherwise, they got a financial penalty. Please stop being a kid who post everywhere you see JVM product your opinion on that. Kafka, Pulsar are two successful projects no matter what you think. Kafka relies on a bit outdated architecture but has the most vibrant ecosystem. Those are major pros and cons. Not a language or VM.

Did you reply to the wrong post?

Redpanda uses the Seastar framework which was created by the ScyllaDB project. Scylla is high-performance C++ reimplemation of Cassandra and RedPanda seems to be chasing the same thing as an alternative to Kafka/JVM.

As a 12 year adtech veteran who has built ad networks from scratch 3 times, low-latency and high-throughput are critical to ad serving infrastructure and that's why Scylla is such a better alternative to Cassandra. The only other database that gets close is Aerospike, and possibly Redis Enterprise with Flash persistence. It's entirely valid to want similar improvements for event streams as well, and as long as they keep the same external API then you don't lose any of the ecosystem advantages either.

who cares about lower percentage tiers in the world of big data? what does the p30 or 50 even matter at large scale?

See Gil Tene's talk on how not to measure latency.

https://www.youtube.com/watch?v=lJ8ydIuPFeU

What matters is what most of your customers will get - p99, p999, p9999, p100.

Ironically, Gil Tene uses the talk to sell you the Azul C4 pauseless GC, which shall easily invalidate your 10x lower p99 latency claim. Of course we also have zgc and shenandoah these days.

You are assuming that all workloads are customer facing.