Eppo vs Split
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 onlyFree tier available
Free tierWhat 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.
Paid tiers are quote-based, priced by monthly tracked keys.
Free tier
Free tier available for small teams.
Free tier with limited monthly tracked keys.
Open source
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Established
Eppo (Datadog) · since 2020
Established
Harness · since 2015
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.
- Automatic metric impact on every flag catches regressions nobody thought to measure.
- Guardrail alerts stop a bad rollout before it reaches everyone.
- Strong data-platform integrations.
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.
- Post-acquisition roadmap now sits inside Harness's broader platform strategy.
- Requires meaningful event instrumentation before the impact analysis is useful.
- Opaque enterprise pricing.
Best for
Data-mature organisations where experiment results must withstand scrutiny.
Teams that want every release measured, not just deliberate experiments.
All of these integrate with: Snowflake, Segment, Slack.
Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.