Statsig vs Eppo
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 tierQuote on request
Quote onlyWhat 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.
Quote-based, generally aimed at companies with a data team and a warehouse already in place.
Free tier
Generous free tier including unlimited feature flags and a large monthly event allowance.
Free tier available for small teams.
Open source
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Widely used
Statsig (Amplitude) · since 2020
Established
Eppo (Datadog) · 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.
- 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.
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.
- 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.
Best for
Product teams that want experimentation and analytics to share one source of truth.
Data-mature organisations where experiment results must withstand scrutiny.
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.