our open source system. We use this tool to serve a custom routing engine at day job. Handles 100req/s djikstra in a 2GB pod, due to precalculation of contraction hierarchies.

> And I only mentioned options. How do you store "every stock quote and options trade in the past 4 years" in 263 GB!?

I think this would be pretty straightforward for Parquet with ZSTD compression and some smart ordering/partitioning strategies.

DuckDB and SQL FTW.

Doesn’t matter. The point is that DuckDB can operate well on a wide range of infrastructure and is well suited for operating in resource constrained environments.

Post to HN apparently

The changelog is remarkable. Thanks to this team for creating such an amazing tool. It's genuinely the technology I've been most excited about in a long time. Makes the ergonomics of working with large data a joy and extremely fast.

IDK, they were sending around stacks of Mac Studios to tinkerer youtubers messing with EXO clustering like @geerlingguy.

https://youtu.be/1iT9JeZYXcI?si=UMR0nfHAYbVq2tF1

How do you ascribe a revenue number like that based on one collection of changes in a huge system? Presumably there were a bunch of other features being released around the same time as it. Was there a lot of A/B testing around it?

Amazon uses a complicated process called "attributed OPS". Meaning you may not be directly responsible for but you contributed in some way.

Doesn’t matter, @ChadMoran is already on the fast track whilst you are on a pip.

Hah, well I've done something right. They've let me stay here almost 15 years.

Ok, but prefill/prompt processing was definitely the weak point before. They were already solid in raw tokens/sec after TTFT

my mac mini m4 is getting to be a good substitute for claude for a lot of use cases. LM Studio + qwen3.5, tailscale, and an opencode CLI harness. It doesn't do well with super long context or complexity but it has gotten production quality code out for me this week (with some fairly detailed instructions/background).