Training a 4B model to produce 81% faster query plans than Postgres
...or how to make Qwen learn query optimization via agentic reinforcement learning
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Summary
pgrust 0.2 is 10x faster than its predecessor, 30% faster than Postgres on OLTP workloads, and 300x faster on the Clickbench analytical benchmark.
The performance gain primarily comes from replacing Postgres' row-at-a-time Volcano model query engine with a batched executor that reduces per-row function call overhead. Additional optimizations include operator fusion and SIMD vectorization to lower CPU and memory bandwidth usage per query.
