← Back to pricing overview

LaunchDarkly vs Split: Feature Management vs Feature Experimentation

Updated 30 March 2026

Both platforms sell feature flags. LaunchDarkly positions as the feature management platform for operational control. Split positions as the feature experimentation platform for data-driven product teams. The overlap is significant, but their strengths point in different directions.

Core Philosophy

LaunchDarkly: Feature Management

LaunchDarkly treats feature flags as an operational tool. Progressive rollouts, kill switches, user targeting, and governance workflows. The focus is on safely releasing features and controlling who sees what in production. Experimentation is available but as a paid add-on.

Best for: Engineering teams that need granular control over feature releases, compliance-heavy environments, and organizations where operational stability is the primary concern.

Split: Feature Experimentation

Split treats feature flags as an experimentation framework. Release a feature to a percentage of users and measure impact on key metrics with statistical significance. The focus is on understanding whether features actually improve outcomes. Feature management capabilities are included but secondary.

Best for: Product teams that make data-driven decisions, companies running frequent A/B tests, and organizations where measuring feature impact is as important as releasing features.

Feature Comparison

FeatureLaunchDarklySplit
Feature flagsComprehensiveComprehensive
Targeting rulesAdvanced (segments, rules, prerequisites)Good (targeting, segments)
Progressive rolloutsPercentage-based with schedulingPercentage-based
Kill switchesOne-click disableOne-click disable
Experimentation / A/B testingAdd-on (MAU pricing)Built-in (included)
Statistical significanceAvailable (extra cost)Built-in
Impact analysisLimitedCore feature
Workflow approvalsPro+Enterprise
Relay proxyEnterpriseNot available
Audit logPro+Available
Custom rolesPro+Enterprise
Edge evaluationYes (Cloudflare, Lambda)Limited

The Experimentation Cost Difference

This is the biggest practical difference in pricing. LaunchDarkly charges for experimentation by MAU. Split includes experimentation in the base price.

For a team of 10 developers with a product serving 100,000 monthly active users:

LaunchDarkly

Seats: 10 x $12 = $120/mo

Experimentation: ~$900 to $2,700/mo

Total: $1,020 to $2,820/mo

Split

Seats: Similar per-seat model

Experimentation: Included

Total: $120 to $240/mo (estimated)

The difference is dramatic for high-traffic products. If experimentation is a primary use case, Split's all-inclusive model is significantly cheaper.

The Recommendation

Choose LaunchDarkly if...

  • Feature release safety is the primary concern
  • You need advanced targeting rules and prerequisites
  • Governance (workflow approvals, audit logs) is required
  • Edge evaluation latency matters
  • Experimentation is secondary or not needed

Choose Split if...

  • A/B testing and impact measurement are primary use cases
  • You want experimentation included without MAU surcharges
  • Your product team drives feature flag decisions
  • Statistical significance is part of your release process
  • You have high MAU and need to control experimentation costs

FAQ

Is Split cheaper than LaunchDarkly?▼
Split and LaunchDarkly have similar per-seat pricing. The key difference is Split includes experimentation features at lower tiers without MAU-based surcharges. For teams that primarily need A/B testing with feature flags, Split can be more cost-effective because experimentation is not an expensive add-on.
What is the main difference between LaunchDarkly and Split?▼
LaunchDarkly focuses on feature management: progressive rollouts, kill switches, targeting rules, and operational governance. Split focuses on feature experimentation: A/B testing with feature flags, statistical significance calculations, and impact analysis. Both do feature flags, but their strengths differ. LaunchDarkly is better for operational feature control. Split is better for data-driven experimentation.
Can Split replace LaunchDarkly?▼
For most teams, yes. Split covers the core feature flag functionality (boolean and multivariate flags, targeting, environments) plus adds experimentation. However, LaunchDarkly has deeper governance features (workflow approvals, relay proxy, custom roles with granular permissions) that large enterprises with strict compliance requirements may need.
Which is better for A/B testing?▼
Split is better for A/B testing. Its experimentation engine includes built-in statistical significance calculations, impact analysis across metrics, and traffic allocation controls. LaunchDarkly's experimentation is an add-on that charges per MAU, making it expensive for high-traffic products. If experimentation is your primary use case, Split provides more value.
Do both support all major programming languages?▼
Yes. Both LaunchDarkly and Split offer SDKs for JavaScript, Python, Java, Go, Ruby, .NET, Node.js, React, iOS, and Android. SDK quality and documentation are comparable. Both support server-side and client-side evaluation.