Choosing a feature flag platform is one of those decisions that feels reversible but rarely is. Once your SDKs are embedded in 40 services, your targeting rules are wired into your release process, and your experimentation pipeline depends on flag evaluation data, switching platforms is a six-figure migration project. The stakes are higher than the typical SaaS purchase, and the comparison content available online is mostly vendor-produced marketing that buries the trade-offs.
This is a genuine, neutral comparison of the three most widely deployed feature flag platforms in 2026: LaunchDarkly, Split.io, and Unleash. Each has distinct strengths, real weaknesses, and a specific team profile that it serves best. The goal is to help you make the right choice the first time.
The market in 2026
The feature flag market has matured significantly. LaunchDarkly remains the enterprise leader with the broadest SDK ecosystem. Split.io has leaned heavily into its experimentation and data platform story, rebranding around "feature delivery" rather than just flags. Unleash continues to grow as the dominant open-source option, now with a commercial tier that competes directly with the hosted platforms on features while offering self-hosted deployment.
Newer entrants like DevCycle, Statsig, and Flipt have carved out niches, but the three platforms compared here represent the most common choices for teams evaluating feature flag infrastructure in 2026. Between them, they cover the vast majority of production deployments.
The comprehensive comparison
Before diving into each category, here is the full comparison table for teams that want the high-level view:
| Category | LaunchDarkly | Split.io | Unleash |
|---|---|---|---|
| Hosting | Cloud only | Cloud only | Cloud or self-hosted (OSS) |
| Open source | No | No | Yes (Apache 2.0) |
| Pricing model | Per-seat + MAU tiers | Per-seat + MTU tiers | Free (OSS) / Per-seat (Pro/Enterprise) |
| Starting price | ~$12/seat/mo (Foundation) | Custom pricing | Free (OSS) / ~$80/mo (Pro) |
| Free tier | 14-day trial | Demo/trial | Unlimited (self-hosted OSS) |
| Server-side SDKs | 14+ languages | 10+ languages | 15+ languages |
| Client-side SDKs | 10+ (JS, React, iOS, Android, Flutter) | 8+ (JS, React, iOS, Android) | 10+ (JS, React, iOS, Android, Flutter) |
| Edge SDKs | Relay Proxy, Edge | Split Proxy | Unleash Edge |
| Experimentation | Built-in (Guarded Rollouts) | Core strength (full stats engine) | Basic (via metrics) |
| Targeting complexity | Advanced (segments, rules, prerequisites) | Advanced (segments, traffic types) | Moderate (strategies, constraints) |
| Approval workflows | Yes (Enterprise) | Yes | Yes (Enterprise) |
| Audit log | Yes | Yes | Yes |
| SSO/SCIM | Enterprise plan | Enterprise plan | Enterprise plan |
| Scheduled flag changes | Yes | Yes | Yes (Pro+) |
| Code References | Yes (ld-find-code-refs) | No native equivalent | No native equivalent |
| Webhooks | Yes | Yes | Yes |
| API coverage | Comprehensive REST API | Comprehensive REST API | Full REST + Admin API |
| Typical eval latency | <15ms (server) / cached (client) | <20ms (server) / cached (client) | <10ms (self-hosted) / <20ms (cloud) |
| Data residency | US, EU, AU | US, EU | Anywhere (self-hosted) |
| SOC 2 / ISO 27001 | Yes / Yes | Yes / Yes | Yes (Enterprise) / Self-managed |
| Max flags (practical) | Thousands | Thousands | Unlimited (self-hosted) |
| Community | Proprietary, large ecosystem | Proprietary, moderate ecosystem | Open-source, active community |
| Best for | Enterprise teams needing breadth | Data-driven teams needing experimentation | Teams needing self-hosting or cost control |
Pricing: The real numbers
Pricing is the category where vendor websites are least helpful. Published prices are starting points, and actual costs vary based on usage, features, and negotiation. Here is what the pricing landscape actually looks like.
LaunchDarkly
LaunchDarkly restructured its pricing in 2025 around three tiers: Foundation, Enterprise, and Federal. The Foundation tier starts around $12 per seat per month and includes core flag management with targeting, segments, and basic experimentation. Enterprise adds approval workflows, SSO/SCIM, custom roles, and advanced security features at a significantly higher price point that is only available through sales conversations.
The critical variable is Monthly Active Users (MAU) for client-side flags. Server-side evaluation is effectively unlimited, but client-side SDKs (JavaScript, mobile) are metered by unique users who receive flag evaluations. For a consumer application with millions of MAUs, this cost can exceed the seat-based licensing by a wide margin.
Realistic annual cost for a 20-engineer team with 500K MAU: $25,000 - $80,000 depending on tier and MAU overages.
Split.io
Split.io uses a similar per-seat model with Monthly Tracked Users (MTUs) as the usage variable. Pricing is not published on their website -- all plans require a sales conversation. In practice, Split tends to price competitively against LaunchDarkly, often slightly lower on the seat component but comparable once MTU costs are factored in.
Split's differentiation is its experimentation engine, which is included in all paid tiers rather than gated behind an enterprise plan. For teams that would otherwise need a separate experimentation tool, Split can be more cost-effective on a total-cost basis.
Realistic annual cost for a 20-engineer team with 500K MTU: $20,000 - $70,000 depending on plan and usage.
Unleash
Unleash's pricing is the most transparent and the most varied. The open-source edition is genuinely free with no usage limits -- you host it yourself and get all core flag management features. The Pro tier at approximately $80 per month adds hosted deployment and a limited number of seats. The Enterprise tier adds SSO, custom roles, change requests, and dedicated support at a per-seat price.
For teams that can self-host, Unleash is dramatically cheaper than LaunchDarkly or Split. The total cost is your infrastructure (a single PostgreSQL database and a Node.js application) plus engineering time for maintenance. For teams on the Enterprise tier, pricing is closer to the commercial platforms but typically still 30-50% less.
Realistic annual cost for a 20-engineer team: $0 (self-hosted OSS) / $960 (Pro) / $15,000 - $40,000 (Enterprise, hosted or self-managed).
Pricing summary
| Team Profile | LaunchDarkly | Split.io | Unleash |
|---|---|---|---|
| 5-person startup | $7,200 - $15,000/yr | Comparable | $0 - $960/yr |
| 20-person mid-market | $25,000 - $80,000/yr | $20,000 - $70,000/yr | $960 - $40,000/yr |
| 100-person enterprise | $100,000 - $300,000+/yr | $80,000 - $250,000+/yr | $40,000 - $150,000/yr |
| High MAU/MTU (>5M) | Add $50,000 - $200,000+/yr | Add $40,000 - $150,000+/yr | No usage-based cost |
Language and SDK support
SDK coverage determines whether a platform can actually serve your entire stack. A platform that covers your backend but not your mobile clients forces you into a multi-platform situation that nobody wants.
LaunchDarkly
LaunchDarkly has the broadest official SDK support in the market. Server-side SDKs cover Go, Java, .NET, Python, Ruby, Node.js, PHP, Rust, C/C++, Haskell, Lua, and Erlang. Client-side SDKs cover JavaScript, React, React Native, iOS (Swift/Objective-C), Android (Java/Kotlin), Flutter, and Electron. The SDKs are mature, well-documented, and consistently updated.
The Relay Proxy handles high-throughput edge cases, allowing you to proxy flag evaluations through your own infrastructure to reduce latency and manage connectivity in restricted environments.
Split.io
Split's SDK coverage is slightly narrower but covers the major languages well. Server-side SDKs include Java, .NET, Python, Ruby, Node.js, Go, and PHP. Client-side SDKs cover JavaScript, React, React Native, iOS, and Android. The SDKs are well-maintained, though some community-contributed SDKs lag behind the official ones in feature completeness.
Split includes a Proxy that serves a similar purpose to LaunchDarkly's Relay Proxy, enabling server-side evaluation in restricted or high-throughput environments.
Unleash
Unleash has the widest language coverage if you include community-contributed SDKs. Official server-side SDKs cover Node.js, Java, Go, Python, Ruby, .NET, PHP, and Rust. Client-side SDKs cover JavaScript, React, iOS, Android, and Flutter. Community SDKs add C++, Swift (standalone), Dart, Elixir, and others. The quality of community SDKs varies, but the official SDKs are production-grade.
Unleash Edge is the proxy layer, designed for low-latency evaluation at the edge. It is written in Rust and is significantly more performant than the earlier Unleash Proxy it replaced.
SDK comparison
| Language/Platform | LaunchDarkly | Split.io | Unleash |
|---|---|---|---|
| Go | Official | Official | Official |
| Java/Kotlin | Official | Official | Official |
| .NET/C# | Official | Official | Official |
| Python | Official | Official | Official |
| Node.js | Official | Official | Official |
| Ruby | Official | Official | Official |
| PHP | Official | Official | Official |
| Rust | Official | Community | Official |
| C/C++ | Official | No | Community |
| JavaScript (browser) | Official | Official | Official |
| React | Official | Official | Official |
| React Native | Official | Official | Community |
| iOS (Swift) | Official | Official | Official |
| Android (Kotlin) | Official | Official | Official |
| Flutter | Official | Community | Official |
| Elixir | No | No | Community |
Hosting and deployment
The hosting question is often the first filter. Some organizations cannot send flag evaluation data to a third-party cloud. Others do not want the operational burden of managing infrastructure. This is where the three platforms diverge most sharply.
LaunchDarkly: Cloud only
LaunchDarkly is exclusively cloud-hosted. Your SDKs connect to LaunchDarkly's infrastructure for flag evaluations, and all flag configuration data lives in LaunchDarkly's systems. The Relay Proxy can be deployed in your infrastructure to reduce external calls, but the source of truth remains LaunchDarkly's cloud.
Strengths: Zero infrastructure management, global edge network, consistent performance, managed uptime SLA.
Limitations: Not suitable for air-gapped environments, flag evaluation data traverses the public internet (encrypted), limited data residency options (US, EU, AU).
Split.io: Cloud only
Split.io is similarly cloud-only. The Split Proxy can be deployed locally for performance, but configuration management and the experimentation engine run on Split's infrastructure.
Strengths: Zero infrastructure management, integrated experimentation pipeline, managed uptime.
Limitations: Same constraints as LaunchDarkly -- no self-hosted option, limited data residency.
Unleash: Cloud or self-hosted
Unleash is the only platform in this comparison that offers true self-hosting. The open-source edition runs on any infrastructure that can host a Node.js application and a PostgreSQL database. The Enterprise edition adds additional features while maintaining the self-hosted deployment option.
Strengths: Complete data sovereignty, deployable in air-gapped environments, no external dependencies, customizable to your infrastructure.
Limitations: Self-hosting requires operational investment (monitoring, upgrades, backups, scaling). The managed cloud option removes this burden but limits some flexibility.
For organizations in regulated industries (healthcare, finance, government), defense contractors, or companies with strict data sovereignty requirements, Unleash's self-hosted option is often the deciding factor regardless of other feature comparisons.
Experimentation and analytics
This is the category where the three platforms differ most in philosophy and depth.
Split.io: Experimentation as a core competency
Split was built with experimentation at its center. The platform includes a full statistical engine with:
- Automated metric impact analysis: Attach any metric to a flag treatment and Split calculates statistical significance automatically
- Sequential testing: Results update in real time with proper statistical corrections for multiple testing
- Traffic allocation controls: Split traffic precisely between treatments with ramping capabilities
- Metric alerting: Automated alerts when a treatment negatively impacts key metrics
- Attribution modeling: Understand the causal impact of a feature, not just correlation
For teams that run frequent A/B tests and need rigorous statistical analysis integrated into their flag platform, Split is the strongest option. The experimentation engine is available on all paid plans, not gated behind an enterprise tier.
LaunchDarkly: Experimentation as an add-on
LaunchDarkly added experimentation capabilities through its Guarded Rollouts feature and expanded experimentation support. The offering includes:
- Metric tracking: Attach metrics to flag variations and track impact
- Statistical analysis: Bayesian statistical engine with automatic significance detection
- Guardrail metrics: Define metrics that must not degrade during a rollout
- Integration with data warehouses: Export experiment data for external analysis
LaunchDarkly's experimentation is capable and improving rapidly, but it is not the platform's primary identity. Teams that need deep experimentation with advanced statistical controls may find Split's dedicated engine more comprehensive. Teams that need basic "does this feature hurt our metrics?" analysis will find LaunchDarkly's experimentation sufficient.
Unleash: Basic metrics, BYO experimentation
Unleash takes a minimalist approach to experimentation. The platform provides:
- Custom metrics: Track impressions and custom events per flag
- A/B variant support: Define multiple variants with percentage allocation
- Metrics API: Export raw evaluation and event data for external analysis
Unleash does not include a statistical analysis engine. The expectation is that teams will pair Unleash with a dedicated experimentation or analytics platform (Amplitude, Mixpanel, an internal data warehouse) and use Unleash for the flag evaluation layer only.
This is a deliberate design choice aligned with Unleash's open-source philosophy: do one thing well (flag management) and integrate with existing tools for adjacent concerns.
Experimentation summary
| Capability | LaunchDarkly | Split.io | Unleash |
|---|---|---|---|
| Statistical engine | Bayesian (built-in) | Frequentist + sequential (built-in) | None (BYO) |
| Auto significance detection | Yes | Yes | No |
| Guardrail metrics | Yes | Yes | No |
| Real-time results | Yes | Yes | Metrics only (no stats) |
| Traffic allocation | Yes | Yes (advanced) | Yes (basic variants) |
| Multi-armed bandit | Limited | Yes | No |
| Data warehouse export | Yes | Yes | Yes (raw events) |
| Depth of statistical analysis | Moderate | Deep | None |
Targeting and segmentation
All three platforms support the core targeting features: individual user targeting, segment-based targeting, and percentage rollouts. The differences emerge in the depth of the targeting rules and the sophistication of the segmentation engine.
LaunchDarkly
LaunchDarkly's targeting is the most flexible. Features include:
- Multi-valued flags: Boolean, string, number, and JSON flag types
- Prerequisite flags: Flag B can only be enabled if Flag A returns a specific value
- Segments: Reusable user groupings based on attributes
- Rule ordering: Multiple targeting rules with explicit priority ordering
- Custom attributes: Target on any attribute you pass to the evaluation context
- Percentage rollouts: Within any rule, allocate traffic by percentage
The prerequisite flag feature is unique to LaunchDarkly and valuable for complex rollout scenarios where features depend on each other.
Split.io
Split's targeting is built around the concept of "traffic types" -- different entities that can be targeted (users, accounts, devices, sessions). Features include:
- Traffic types: Target different entity types independently
- Targeting rules: Attribute-based rules with AND/OR logic
- Segments: User groupings, importable via CSV or API
- Percentage allocation: Fine-grained traffic splitting
- Dependent splits: Similar to LaunchDarkly's prerequisites
- Kill switch: Instant treatment override for emergencies
The traffic type system is a genuine differentiation. If your product serves multiple entity types (users within accounts, devices within users), Split models this natively.
Unleash
Unleash uses an "activation strategy" model that differs from the rule-based approach of the commercial platforms:
- Strategies: Predefined evaluation strategies (standard, gradual rollout, user IDs, IPs, hostnames)
- Custom strategies: Define your own evaluation logic
- Constraints: Add attribute-based conditions to any strategy
- Segments: Reusable constraint groups
- Variants: Multiple return values with percentage allocation
Unleash's strategy model is simpler than LaunchDarkly or Split's rule engines, which is both a strength (easier to reason about) and a limitation (less expressive for complex targeting scenarios). Custom strategies provide an escape hatch, but require SDK-level implementation.
Integrations and ecosystem
LaunchDarkly
LaunchDarkly has the broadest integration ecosystem:
- CI/CD: GitHub Actions, Terraform, Pulumi, Bitbucket Pipes, CircleCI, Jenkins
- Observability: Datadog, New Relic, Honeycomb, Dynatrace, Splunk, Elastic
- Collaboration: Slack, Microsoft Teams, Jira, ServiceNow
- Data: Snowflake, BigQuery, Redshift, Segment
- Developer tools: VS Code extension, IntelliJ plugin, Code References CLI
The Terraform provider is particularly valuable for teams managing flag infrastructure as code. The IDE extensions provide real-time flag information while coding.
Split.io
Split's integration set focuses on the data and experimentation workflow:
- CI/CD: GitHub Actions, Terraform, Bitbucket
- Observability: Datadog, New Relic, Splunk, Sumo Logic
- Collaboration: Slack, Jira
- Data: Segment, mParticle, Google Analytics, Amplitude
- Developer tools: CLI, Admin API
Split's analytics integrations are the standout. The platform can ingest metrics from your existing analytics tools and correlate them with flag treatments automatically, which reduces the instrumentation effort for experimentation.
Unleash
Unleash's integration set is growing but more focused:
- CI/CD: GitHub Actions, Terraform, GitLab CI
- Observability: Datadog (via API), custom integrations via webhooks
- Collaboration: Slack, Microsoft Teams, webhook-based integrations
- Data: Custom via API/webhooks
- Developer tools: CLI, Admin API, OpenAPI spec
Unleash's integration model relies more heavily on its API and webhook system. The trade-off is that most integrations require light configuration rather than being pre-built, but the API is well-documented and the webhook system is flexible enough to integrate with virtually any tool.
Community, support, and longevity
LaunchDarkly
LaunchDarkly was founded in 2014 and has raised approximately $330 million in venture capital. The company is well-established with a large customer base (over 4,000 companies) and is unlikely to disappear. Support tiers range from community forums and documentation (Foundation) to dedicated support engineers and SLAs (Enterprise).
The documentation is excellent -- among the best in the developer tools space. SDKs have detailed guides, migration paths, and code examples for every supported language.
Split.io
Split was founded in 2015 and was acquired by Harness in 2024. The platform continues to operate as a product within the Harness suite, with plans for deeper integration into Harness's software delivery platform. This acquisition introduces both opportunity (broader platform integration) and risk (product direction influenced by parent company priorities).
Documentation is solid and improving. Support follows a similar tier structure to LaunchDarkly.
Unleash
Unleash was created in 2015 at FINN.no (Norway's largest online marketplace) and open-sourced from the start. The company behind it, Unleash, raised funding to build the commercial tiers while maintaining the open-source core. The open-source edition has an active community with regular contributions.
The open-source model provides a unique longevity advantage: even if the company changes direction, the codebase is Apache 2.0 licensed and can be forked and maintained by the community. This is a meaningful consideration for organizations that prioritize vendor independence.
When to choose each platform
Choose LaunchDarkly when
- You are an enterprise team that needs the broadest SDK support, deepest targeting capabilities, and most mature governance features
- You have complex flag dependencies where prerequisite flags and multi-environment coordination are essential
- Your organization requires SOC 2, ISO 27001, and enterprise security features out of the box
- You want the richest integration ecosystem with native connections to your existing CI/CD, observability, and collaboration tools
- Developer experience matters and you value IDE extensions, Code References, and comprehensive documentation
- Budget is not the primary constraint -- you are optimizing for capability and productivity, not cost
Choose Split.io when
- Experimentation is a core part of your product strategy and you need a platform where flag management and statistical analysis are deeply integrated
- You already use or plan to use Harness and want a unified software delivery platform
- You need sophisticated traffic type modeling for products with multiple entity types (users, accounts, devices)
- Data-driven decisions are central to your culture and you want experiment results accessible to product managers and data scientists, not just engineers
- You want strong experimentation without a separate tool -- Split replaces both a feature flag platform and an experimentation platform
Choose Unleash when
- Self-hosting is a requirement due to regulatory, security, or data sovereignty constraints
- Cost is a primary concern and you want production-grade flag management without a per-seat SaaS cost
- You have strong DevOps capabilities and are comfortable operating your own infrastructure
- Vendor independence matters and you want the assurance of an open-source, Apache 2.0 licensed codebase
- You prefer composable tooling -- using Unleash for flags, a separate tool for experimentation, and your own analytics for metrics
- You are a startup or small team that needs feature flags today but cannot justify $20,000+/year
The decision matrix
For teams that want a structured evaluation, score each criterion on a 1-5 scale based on your team's priorities:
| Criterion | Weight (Your Priority) | LaunchDarkly | Split.io | Unleash |
|---|---|---|---|---|
| Pricing / TCO | ___ | 2 | 3 | 5 |
| SDK breadth | ___ | 5 | 3 | 4 |
| Experimentation depth | ___ | 3 | 5 | 1 |
| Targeting sophistication | ___ | 5 | 4 | 3 |
| Self-hosting option | ___ | 1 | 1 | 5 |
| Enterprise governance | ___ | 5 | 4 | 4 |
| Integration ecosystem | ___ | 5 | 4 | 3 |
| Community / open source | ___ | 1 | 1 | 5 |
| Documentation quality | ___ | 5 | 4 | 4 |
| Ease of setup | ___ | 4 | 4 | 3 (cloud) / 2 (self-hosted) |
Multiply each score by your weight, sum the results, and the highest total indicates your best fit. No single platform wins across all criteria -- the right choice depends entirely on what matters most to your team.
What none of them solve: The cleanup problem
There is one problem that all three platforms share, and it is worth stating directly: none of them remove stale flag code from your codebase.
LaunchDarkly, Split, and Unleash are all excellent at managing the first half of the flag lifecycle -- creation, targeting, rollout, and experimentation. They tell you which flags exist, how they are configured, and who is evaluating them. Some offer visibility into where flags appear in code (LaunchDarkly's Code References) or mark flags as stale (Unleash's lifecycle markers).
But when a flag reaches 100% rollout and it is time to clean up the code, every team faces the same problem regardless of platform:
- The
if/elsebranches remain in your codebase - The dead code path still ships to production
- The test cases for the disabled path still run in CI
- The conditional imports and unused dependencies persist
This is not a failing of these platforms. Flag management and flag cleanup are fundamentally different problems. Management is a runtime concern (evaluating flags at request time). Cleanup is a code transformation concern (parsing syntax trees, removing dead branches, generating safe refactoring PRs).
In our experience, it is common for enterprise codebases to accumulate several stale flags each month. After a year, the number of flags that are "done" in your management platform but still polluting your code with dead conditionals can easily reach into the dozens or hundreds. The management platform shows a clean dashboard. The codebase tells a different story.
This is where dedicated cleanup tooling fits into the picture. Tools like FlagShark work alongside whatever management platform you choose -- LaunchDarkly, Split, Unleash, or any other -- by monitoring your repositories for flag usage via tree-sitter AST parsing, tracking the lifecycle of each flag from the moment it appears in a pull request, and generating cleanup PRs when flags become stale. The management platform handles creation through rollout. The cleanup tool handles staleness through removal.
The platform you choose for flag management matters. But equally important is having a strategy for what happens after the rollout is complete. The best feature flag setup in 2026 is not just the right management platform -- it is the right management platform paired with a cleanup workflow that prevents dead flags from accumulating in your code.
Whichever platform you choose, the most important decision is making it deliberately based on your team's actual needs rather than defaulting to the most recognizable name. LaunchDarkly is the best platform for many teams. Split is the best for others. Unleash is the best for others still. Understand what you need, evaluate honestly, and invest in the full lifecycle -- management and cleanup -- from day one.