Hey, very inspiring article, Redis engineer here. How do you work with static allocation on variable query structure, and row counts that can explode depending on the data shape?

And isn't there a benefit for small allocations on advanced memory allocations that you can't leverage if all is working in big page allocations? Do you implement memory allocations from scratch or leveraging existing allocator on top of these memory blocks strategy somehow?

If one has a TigerBeetle cluster with high inter node latency, are there any easy wins to lower the latency of the whole cluster left? My head hurts when I think of latency in large clusters, so your work this year with latency was inspiring.

EDIT: I guess part of the question is about the problems with clusters with >130ms latency and if there are challenges you consider easy.

Hey Joran, awesome stuff. I see a TB post every now and then and it seems like such an interesting problem space to work in. I'm all the way at the other end of the stack, most software we write day-to-day is in JVM-based languages where you don't have to think about these things at all (we get by with ms latencies instead of ns). Reading this post inspires me explore low-level engineering more and I figure zig or rust would be a good place to start.

What are some interesting problems or things you can think of to work on that would give someone new a nice amount of exposure to this kind of programming?

How has AI changed the way that TigerBeetle does software engineering? Given the project’s idiosyncratic language/memory allocation choices, it’s an interesting data point how well the frontier models work for you guys.

Great and interesting work !

What use cases is Tiger Beetles architecture not a good fit for?

When tiger beetle becomes pluggable to different use cases, how should I think about "do I want tiger beetle?"