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Comment by NaomiLehman | Hacker News Reader

M silicon/SoC is the best thing to happen to computing, for me.

I have 64GBs of RAM in my Macbook Pro. I load a 48GB DuckDB to RAM and run real-time, split-second, complex, unique analysis using Polars and Superset. Nothing like this was possible before unless I had a supercomputer.

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Is it really that much better than some small form AMD Ryzen with 2x32 SODIMM thrown in? I get that the M series is amazing in terms of efficiency and some people love Apple hardware but you could likely have had that performance with a $700 setup.

The only server that actually matched the performance of a Mac Studio was XEON Max series (formerly codenamed Sapphire Rapids HBM) with 64GB of integrated memory into the CPU package. the latency between the CPU and RAM is simply too big in a regular PC.

for DB's bandwith to RAM and Storage is just as important.

that's the thing. latency to RAM is everything. I would take 10x lower bandwidth in RAM vs 100x better latency from CPU to RAM.

The only x86 CPU that does this is the Xeon Max: https://www.intel.com/content/www/us/en/products/details/pro...

There are other possible solutions but they are expensive.

the problem with Macs, among other things, is lack of ECC RAM.

Have you tried other PC with 64 GB of RAM?

yes. we have PCs. AFAIK, the cheapest PC that compares for my workflow is an EPYC/NUMA or another very expensive CPU/latency optimized server. We have a complex stack, with clients running unique queries that we can't predict and gigabytes loaded into RAM, L3 cache doesn't always save us. I haven't found another solution, I wish we could drop the Macs cause the OS is pretty awful.

We're using Macs as servers. But it's a small operation.

i'm guessing you're using macs newer than M2, so they can't run linux; but i wonder if fedora server (asahi remix) would suit your operation well

we also tried Asahi on M2 Ultras but we had big performance issues on the DBs compared to Mac OS.

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