The type of ADHD I have seems to have an "autonomic nervous system impairment" component and a symptom profile overlapping with hyperadrenergic POTS.
1. I respond much better to Guanfacine ER (GFC) than stimulants alone (currently complementing with Vyvanse (LDX) 40mg, but I'd rate the Guanfacine as critical)
2. My blood pressure is very volatile, and GFC is supposed to have an impact but did not in my case, at least initially. I'd take GFC at bedtime and LDX in the morning, and on ChatGPT's suggestion, I asked my psych if I could take them together in the morning. Gamechanger for my blood pressure: the explanation seems to be that LDX makes my sympathetic nervous system extra simulated (on top of a poor baseline), and co-timed GFC balances it out.
3. I have poor cardiac endurance, and I find running nearly impossible. I'm a healthy young male who does weights and all. At ChatGPT's suggestion, I wore a Polar H10 and measured my resting heart rate while sitting, and then while standing still. I get a jump from 80bpm to 115bpm-ish, a strong indicator for something orthostatic.
I'm currently exploring rowing (with a concept2). I don't know why but it has a strong impact on my mental state that goes beyond general exercising: something about the rhythmic entrainment it produces, while being recumbent (good for POTS).
Prior to July 2025 (ClickHouse v25.7), ClickHouse did not support UPDATE statements. At all. Like most columnar, analytics databases. We spent a lot of effort designing and implementing a way to support high-performance, SQL-standard UPDATE statements. This test was pretty much just trying to see how good of a job we had done, by comparing ourselves to the gold standard, Postgres. (If you're curious, we also wrote about how we built the UPDATE support in depth https://clickhouse.com/blog/updates-in-clickhouse-2-sql-styl...)
We have some updates to the post in progress; we originally deliberately used cold runs for both ClickHouse & Postgres, because we wanted to look at the "raw" update speed of the engine, vs. the variability of cache hits. But TL;DR when you run a more "real world" test where caches are warm and Postgres is getting very high cache-hit ratio, its point updates are consistently ~2ms, while ClickHouse is somewhere ~6ms (bulk updates are still many multiples faster in ClickHouse even with the cache in play).
A test that would show PG's strengths over ClickHouse for OLTP would be a stress test with a long-running set of updates.
ClickHouse maintains updates as uncompacted patches merged in the background, which is how you would do it with a columnar store. But if you have an update-heavy workload, these patches would accumulate and your query performance would start to suffer. PG on the other hand completes all update work inline, and wouldn't get degrading performance under update-heavy regimes.
This is just a fundamental artifact of OLAP vs OLTP, maybe OLAP can be optimized to the point where it doesn't really matter for most workloads, but a theoretical edge remains with row-based stores and updates.