VeltrixDB's I/O layer runs in polling mode — the engine continuously monitors the completion queue rather than waiting for kernel interrupts. Under sustained write load this eliminates wakeup overhead entirely, flattening tail latency at the I/O boundary where most databases lose P99 predictability.

VeltrixDB's GC engine ranks VLog entries by access temperature before deciding what to compact. Hot data is never relocated during a GC pass — only cold entries move. GC runs without competing for the NVMe bandwidth live reads depend on, and emergency compaction runs have dropped to zero in sustained benchmarks.

VeltrixDB pins its compaction thread to a reserved CPU core. Compaction work never contends with request-handling threads for scheduler time — the intermittent P99 tail spikes that appear under heavy writes on shared-core designs simply don't exist in this architecture.

A built-in BPF program watches CPU throttle counters in real time and signals VeltrixDB's GC scheduler before a throttle event hits the write path. Sustained write peaks stay smooth — hard stalls become gradual backpressure, and the GC emergency counter stays at zero even on resource-constrained nodes.

VeltrixDB's tiering engine automatically moves data that hasn't been accessed in over 5 minutes to object storage, rate-limited to avoid I/O contention. The NVMe index stays hot. Cold data lands on S3, GCS, or Azure at a fraction of NVMe cost — no manual configuration required, and the GC engine is aware of tiered entries so it never relocates them unnecessarily.