Skip to content
testcritic

Eppo vs Statsig

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

Quote on request

Quote only

Free tier available

Free tier

What drives the bill

The metric that actually scales your invoice.

Quote-based, generally aimed at companies with a data team and a warehouse already in place.

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

Free tier

Free tier available for small teams.

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

Open source

Self-hostable

No-code authoring

Languages

JavaScriptTypeScriptPythonJavaGoRuby
JavaScriptTypeScriptPythonJavaC#GoRubySwiftKotlin

Platforms

WebAPIiOSAndroid
WebAPIiOSAndroid

Fits teams

Scale-up / mid-marketEnterprise
StartupScale-up / mid-marketEnterprise

Adoption

Established

Eppo (Datadog) · since 2020

Widely used

Statsig (Amplitude) · since 2020

Strengths

  • Statistically rigorous — sequential testing, CUPED and diagnostics are core, not add-ons.
  • Metrics defined once in the warehouse and reused across every experiment.
  • dbt integration fits existing analytics engineering workflows.
  • 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.

Limitations

  • Requires a warehouse and a data team; not usable by a product manager alone.
  • Feature-flagging capability is lighter than dedicated flag platforms.
  • Now part of Datadog, which changes the strategic picture.
  • 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.

Best for

Data-mature organisations where experiment results must withstand scrutiny.

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

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

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