Valkey achieved one million RPS 6 months after forking from Redis

One thing the article doesn’t mention is how they figured out that waiting for external memory access is the bottleneck. Are there any profiling tools available that would tell the developer that the cpu is waiting for external memory x% of the time?

This is really cool work! I am surprised to see this level of tuning without using cache profiling or other performance counters to identify the bottleneck and quantify the improvement.

Redis&#x27; biggest flaw is its single threaded design. We end up having to run separate redis processes on each core and have client side sharding. We&#x27;re lucky that our data allows this.<p>We experiment with KeyDB too but I&#x27;m not sure what state that project is in.

Great to see Valkey team is making a progress well beyond keeping old Redis version Security Patched.

Who in their right mind uses linked lists for a database style workload? Try doing this with arrays to get a reasonable baseline.

Nice, how does that compare with Pedis, which was written in C++ several years ago? It&#x27;s an incomplete Redis lookalike that isn&#x27;t getting current development, but it uses Seastar, the same parallelism framework as ScyllaDB.<p><a href="https:&#x2F;&#x2F;github.com&#x2F;fastio&#x2F;1store">https:&#x2F;&#x2F;github.com&#x2F;fastio&#x2F;1store</a>

The interleave thing isnt intuitive to me.<p>The problem with linked lists is the memory address of nodes isn&#x27;t necessarily contiguous because of malloc and the value could be NULL? Why does interleave loop make it faster for the cpu? It still a linked list, arbitrary memory, could be NULL? Not sure what im missing here?