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testcritic

Split vs LaunchDarkly

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.

Paid tiers are quote-based, priced by monthly tracked keys.

LaunchDarkly has dropped per-seat pricing: Developer is free with unlimited seats, and Foundation is pay-as-you-go on service connections and client-side monthly active users with no platform or seat fee. High-traffic consumer products still get expensive, but now through MAU rather than seats. Enterprise is quote-based.

Free tier

Free tier with limited monthly tracked keys.

Developer plan is free forever with unlimited seats.

Open source

Self-hostable

No-code authoring

Languages

JavaScriptTypeScriptPythonJavaC#GoRubyPHPSwiftKotlin
JavaScriptTypeScriptPythonJavaC#GoRubyPHPSwiftKotlin

Platforms

WebAPIiOSAndroid
WebAPIiOSAndroidDesktop

Fits teams

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

Adoption

Established

Harness · since 2015

Category standard

LaunchDarkly · since 2014

Strengths

  • 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.
  • Extremely reliable flag delivery with offline fallbacks — this is infrastructure you can trust in the request path.
  • Best-in-class governance: approval workflows, audit logs, role-based access.
  • Code references and stale-flag detection actually help you remove dead flags.

Limitations

  • Post-acquisition roadmap now sits inside Harness's broader platform strategy.
  • Requires meaningful event instrumentation before the impact analysis is useful.
  • Opaque enterprise pricing.
  • Still the expensive option once client-side MAU volume is real, even after the move off per-seat pricing.
  • Experimentation is competent but less sophisticated than dedicated statistics platforms.
  • Usage-based billing on service connections and MAU is harder to forecast than a seat count.

Best for

Teams that want every release measured, not just deliberate experiments.

Engineering organisations where flags are critical infrastructure and governance is required.

All of these integrate with: Segment, Datadog, Snowflake, Slack, Jira, New Relic.

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