WhyLabs profiles your data efficiently with whylogs and watches drift across large volumes without moving raw data around — a genuine strength at scale — while ValidAnytime is the narrower, complementary alarm layer on the metrics you care about. It wraps each stream in an anytime-valid alarm you can check continuously, with a shared false-alarm budget across every one.
| Capability | ValidAnytime | WhyLabs |
|---|---|---|
| Valid under continuous monitoring (unlimited peeking) | YesAnytime-valid by construction — Ville's inequality bounds the false-alarm rate at every look at once. | NoFixed thresholds and fixed-n tests inflate false alarms the more often you check. |
| Fleet-wide false-alarm control (online FDR) | YesA false-discovery budget shared across every stream, not per-alert luck. | NoAlerts are configured per-metric; no global bound on false discoveries. |
| Per-alarm statistical certificate | YesEvery alarm ships a guarantee tag and a theorem reference — you can audit why it fired. | NoAn alert tells you a line was crossed, not what its error guarantee is. |
| Prove it on your own history before committing (backtest gate) | YesReplay your past data: a config only ships if it stays quiet on normal history and fires on a real regression. | PartialYou can chart history, but there is no gate that validates a detector's error behaviour before it goes live. |
| Lightweight data profiling at scale | PartialWe ingest the metric values you compute; we do not profile raw datasets for you. | Yeswhylogs profiles large data volumes efficiently without exporting raw rows — a real strength. |
| Built-in drift & data-quality monitors | PartialWe focus on trustworthy change-detection on the streams you send, not a broad monitor catalog. | YesPreset drift, data-quality, and distribution monitors out of the box. |
| Continuous checking without inflating false alarms | YesCheck as often as you like — Ville's inequality holds the false-alarm rate across all looks at once. | PartialMonitors are configured per-feature on batch profiles; there is no valid-under-peeking guarantee. |
We are not trying to be a dashboard, a tracer, or a platform. If you need these, reach for the right tool — often alongside ValidAnytime.
A comparison table is claims; behavior is measurable. The honest drift-detector benchmark replays every detector we ship — including the classical control-chart rules most monitoring stacks alert with — against labeled synthetic breaks, and the detector guides explain each rule, where it wins, and where it lies.
Replay your own history through the backtest gate and see whether — and at which point — ValidAnytime would have caught your regression. Free, in minutes.
Comparison based on public documentation as of July 2026; corrections welcome — email hello@validanytime.com. Source: WhyLabs docs