That doesn’t make sense. Memory can’t be slower than disk - disk is either 
physical, or memory backed - which means its upper speed limit is the memory 
speed limit.

If the presentation means to imply that ethernet is so fast - faster than 
memory busses themselves - that you could fan out to achieve speed faster than 
memory - that doesn’t make help - because either it is DMA - going to disk 
(which is slower), or going to the CPU - which can only read memory at the 
speed of the memory bus.

You could theoretically achieve “ultra speeds” with multicasting, on a super 
fast ethernet bus - but the source is still probably limited to memory speeds.

So the abstract you provided doesn’t jive with me.

> On May 24, 2025, at 7:06 PM, Jason E. Aten <j.e.a...@gmail.com> wrote:
> 
> This is an amazing talk from last year 2024 March 22 Qcon from
> the TigerBeetle CEO, Joran Greef. Zig has lessons for Go.
> 
> "Redesigning OLTP for a New Order of Magnitude"
> https://www.infoq.com/presentations/redesign-oltp/
> 
> Early on the talks covers that latest trends in memory vs network vs disk,
> (hint: at 800GB ethernet means memory is now the bottleneck, and
> it is slower than disk(!)).
> 
> Greef also talks about Deterministic Simulation Testing (DST) and 
> gives a highly compelling demo for why you want it.
> 
> He points out that replication algorithms like Paxos and Raft, and points
> out that a single sector fault on one machine can create global 
> data loss. Yikes.
> (See 35 minutes in)
> 
> Again, the video at 35:00 gives a very strong critique of Raft vs VSRR
> 
> arguing raft too simple/inappropriate (assumes perfect disks)
> 
> and for actual faulty disks can get blocked and not be fault
> 
> tolerant at all. They use VSRR in TigerBeetle, plus NASA/Fortran
> 
> style "pre-allocate all memory". 
> 
> 
> 
> TigerBeetle is Apache 2 open source. It is written in Zig but has
> 
> lessons for software using Go throughout.  His discussion of
> 
> optimizing write compaction in LSM trees is fascinating, 
> 
> as is integrating consensus with replication (2018 best paper
> 
> at FAST from Alagappan et al), and using 
> 
> speculative replicated state machine
> 
> execution to avoid stalling on bad storage sectors -- I
> 
> expect all of these to be the future of databases.
> 
> 
> 
> Five stars.
> 
> 
> 
> Enjoy,
> 
> Jason
> 
> 
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