On benchmarking

This post introduces best practices for benchmarking databases, focusing on client-server architecture, resource selection, workload definition (traffic ratios, data distributions), open vs. closed loop benchmarks, and key metrics like throughput (QPS/TPS) and latency (percentiles). It emphasizes the importance of fair resource allocation, realistic workload simulation, and comprehensive measurement to avoid biased results.