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testcritic

Statsig vs PostHog

Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.

Entry price

Free tier available

Free tier

Free tier available

Free tier

What drives the bill

The metric that actually scales your invoice.

One of the most generous free tiers in developer tooling; paid usage is billed on analytics events, not seats.

Usage-based pricing per product with a substantial free tier; most small teams stay free indefinitely.

Free tier

Generous free tier including unlimited feature flags and a large monthly event allowance.

Large monthly free allowance across every product, plus free self-hosting.

Open source

MIT (core) / proprietary enterprise modules

Self-hostable

No-code authoring

Languages

JavaScriptTypeScriptPythonJavaC#GoRubySwiftKotlin
JavaScriptTypeScriptPythonJavaGoRubyPHPSwiftKotlin

Platforms

WebAPIiOSAndroid
WebAPIiOSAndroid

Fits teams

StartupScale-up / mid-marketEnterprise
Solo / side projectStartupScale-up / mid-marketEnterprise

Adoption

Widely used

Statsig (Amplitude) · since 2020

Widely used

PostHog · since 2020

Strengths

  • Statistics engine is genuinely strong — sequential testing and CUPED are not marketing veneer.
  • Flags, experiments and analytics in one system removes a whole class of integration work.
  • Warehouse-native mode satisfies data-governance requirements.
  • Replaces four or five separate subscriptions with one bill and one SDK.
  • Free tier is large enough for real production use at startup scale.
  • Open source with a credible self-hosting path.

Limitations

  • Event-based pricing can escalate sharply on high-volume products.
  • Broad surface area means a real learning curve.
  • Changed hands twice in under a year — OpenAI acqui-hired the founding team in September 2025, and Amplitude took over the product and brand in May 2026, so the roadmap is still settling.
  • Individual modules are less deep than category specialists.
  • Self-hosting at scale is a serious infrastructure undertaking.
  • The product surface changes fast, which means occasional churn.

Best for

Product teams that want experimentation and analytics to share one source of truth.

Startups and scale-ups consolidating analytics, replay and flags into one platform.

All of these integrate with: Snowflake, BigQuery, Segment, Slack.

Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.