GrowthBook vs Statsig

GrowthBook

Experiments are defined on feature flags and delivered through 24+ SDKs across server, client, mobile and edge, with inline server-side tests that need no third-party requests, mutual exclusion through namespaces, holdouts, sticky bucketing, bandits and multivariate tests, and visual and URL-redirect tests that can be evaluated at the edge before HTML ships. That is most of a modern programme from one platform. We found no public information on personalisation that can itself be tested, or on a documented lifecycle from hypothesis to archived result with a searchable library of past experiments, which is what holds this below the top of the scale.

Statsig

This is the shape I want: feature flags, experiments and product analytics in one platform, with layers for mutual exclusion, holdouts, autotune, a no-code editor and 30-plus open-source SDKs in almost every language, so server-side delivery is a first-class path. What holds it back from the top end: we found no public information on edge or CDN delivery, and most of the evidence is a feature grid rather than documentation showing how these pieces work together.

GrowthBook

Both engines are documented down to the mechanics — a Bayesian default with an improper prior you can switch for a proper Normal prior, two-sample t-tests for relative change on the frequentist side, and your choice of Holm-Bonferroni or Benjamini-Hochberg correction with the test family spelled out. Guardrails are real: CUPED on both engines, sample ratio mismatch detection, multiple-exposure and suspicious-uplift checks, guardrail metrics, power analysis and minimum data requirements so an early read cannot be dressed up as a conclusion. The implementation is open source and every query is visible SQL in your own warehouse, so a result is reproducible; the gaps are small — corrections exist only for the frequentist engine, and adjusted p-values come out in the UI and CSV rather than through the API.

Statsig

Sequential testing, CUPED, Bonferroni and Benjamini-Hochberg corrections, winsorization and power analysis are all named — a real defence against peeking, variance and multiple comparisons. But we found no public information on sample ratio mismatch detection or guardrail metrics that can stop a harmful test, and the techniques appear as names on a pricing page with no documented assumptions behind them.

GrowthBook

The mechanics are genuinely consent-aware: assignment is stateless consistent hashing so variants serve with no cookie at all, a documented setting defers writing the first-party visitor cookie until consent, a custom event triggers persistence once consent is given, and sticky bucketing can be enabled per visitor only when consent is observed. Against that, the visitor cookie is persisted on page load by default, the privacy notice states Do Not Track signals are not honored, and we found no public information on consent management platform integrations, cookie lifetimes, or IP anonymisation.

Statsig

The consent-relevant content we found is Amplitude's site-wide privacy notice naming essential, performance, functionality and advertising cookies plus web beacons — and an advertising category is an odd companion for a test script. We found no public information on what the Statsig script does before consent, any consent management platform integration, a cookieless or consent-pending mode, or cookie lifetimes.

GrowthBook

The edge path is documented end to end — flags and visual experiments evaluated on the edge so variations ship before the browser paints, URL redirects without flicker, SDK injection with a hydrated payload so the front-end makes no extra network calls — and the docs are unusually honest that the default edge setup makes a blocking payload fetch per request, with two documented ways to remove it: a webhook push into an edge key-value store or a just-in-time payload cache. Self-hosters can run the proxy on their own CDN, and SDK endpoints are scoped to a project and environment. We found no published figures for script weight or Core Web Vitals impact, which is what keeps this from scoring higher.

Statsig

The one performance figure published is post-init evaluation latency under 1 millisecond, which describes SDK evaluation speed rather than what the snippet costs the page. We found no public information on script weight, flicker handling, Core Web Vitals impact or a self-hosting option; warehouse-native deployment is the evidenced alternative path for flicker-sensitive pages.

GrowthBook

This is the model I want: metrics are SQL against Snowflake, BigQuery, Databricks or Redshift, every query is visible and reproducible, no personal data leaves the warehouse, and results are computed in the warehouse the team already trusts rather than in a black box. The REST API is versioned and deep enough to build internal tooling on — create experiments, toggle features from a deploy script, pull the latest analysis into your own reporting, define fact metrics, segments and saved groups — with webhooks and an MCP server on top. We found no public information on stated API rate limits or CDP integrations.

Statsig

Warehouse-native is the headline I care about: run Statsig in your own warehouse, with warehouse ingestion, data warehouse imports, outgoing integrations and a data export API named alongside it. We found no public information on CDP integration for audiences, stated API limits, or full historical experiment export in open formats.

GrowthBook

Hosted is American end to end: a California entity with Santa Clara venue, AWS hosting, a privacy notice that says information is held by providers in the United States and asks users to consent to transfer and processing there, US AI providers as subprocessors, and website terms offering the service only to persons located in the United States. The escape hatch is real and documented — full self-hosting including air-gapped deployment, and warehouse-native mode where no personal data leaves your infrastructure — but the contracting entity is a California company, and we found no public information on EU data residency for the hosted service or a data processing agreement covering the visitor data the script collects.

Statsig

The chain runs through American entities — Amplitude, Inc. in San Francisco on the privacy notice, Washington State law governing the terms, and a notice that personal data may be transferred to the United States with consent, backed by standard contractual clauses. EU hosting appears only within the enterprise warehouse-native deployment, and the subprocessor names we found — Google for login and Stripe for payments — sit in Amplitude's site-wide notice rather than a Statsig-specific list.

GrowthBook

Seat pricing with published usage ceilings and overage rates makes the cloud invoice derivable: Starter is free, Pro is $40 / seat / month for up to 30 users, CDN requests are 2M/mo (then $10/M), bandwidth is 20GB/mo (then $1/GB), and the managed warehouse is 2M events/mo (then $30/M), with experiments and feature flags unlimited on every plan. Enterprise is a sales conversation, and we found no public information on minimum term or VAT treatment, so full annual computability stops at the Pro tier.

Statsig

The free and Pro tiers are genuinely computable: $150 per month with 5 million events included and $0.05 per 1K events after, plus dedupe windows, the rule that 0 or 100 percent rollouts aren't charged, tax treatment and one-month auto-renewal terms all published. The enterprise tier — where warehouse native, SSO and standalone analytics sit — is "Custom" on event or experiment based contracts, so that invoice remains a sales conversation.