Just adding my benchmarking repo, that contains terraform code and scripts using which I performed the benchmarks, helpful for re-evaluating and verifying the numbers published on our website. And possibly to learn where we might have gone wrong.
Pipelined throughput that high usually means the loadgen is the thing you're measuring. Past ~5M ops/sec we needed 3 separate memtier hosts to keep the client off the critical path. Any p99 numbers alongside it?
Yes, for building test cases, for code refactoring, and commenting, because it writes cleaner code, but yeah design decisions were mine. The benchmarks I ran were what dragonfly advertises, so scripts for those were written with AI. For redis compatibility, we run redis’ own unit test and e2e test suite with every change to make sure I am not breaking anything each change and you can review it in the repo.
How does this compare and benchmark with https://github.com/apache/kvrocks
Just adding my benchmarking repo, that contains terraform code and scripts using which I performed the benchmarks, helpful for re-evaluating and verifying the numbers published on our website. And possibly to learn where we might have gone wrong.
https://github.com/kividbio/kivi-benchmark
Pipelined throughput that high usually means the loadgen is the thing you're measuring. Past ~5M ops/sec we needed 3 separate memtier hosts to keep the client off the critical path. Any p99 numbers alongside it?
Has there been heavy usage of AI in building this?
Yes, for building test cases, for code refactoring, and commenting, because it writes cleaner code, but yeah design decisions were mine. The benchmarks I ran were what dragonfly advertises, so scripts for those were written with AI. For redis compatibility, we run redis’ own unit test and e2e test suite with every change to make sure I am not breaking anything each change and you can review it in the repo.
there's a .claude/ in the gitignore
Yes correct