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Flaggr vs Statsig
Experimentation-first — flags bundled into a product-analytics platform
Statsig leads with experimentation — feature flags are one surface of a broader stats platform. If your primary need is rigorous A/B testing with a managed stats engine, it's a serious contender.
Side by side
| Area | Flaggr | Statsig | |
|---|---|---|---|
| Licensing | Open-source (MIT), self-hostable | Proprietary SaaS | flaggr |
| Protocols | REST, Connect-RPC, gRPC-Web, OFREP, SSE | REST + SDK | flaggr |
| Experimentation | Experiments, bandits, toggle-impact analysis | Industry-leading stats engine | them |
| Observability | OTel + Prometheus + Grafana built in | Built-in product analytics | |
| Self-hosting | Helm chart, full stack in your VPC | Not available | flaggr |
| AI agent support | Native MCP server | No public MCP surface | flaggr |
| Pricing | Open-source; usage-based hosted | Event-volume pricing scales steeply | flaggr |
Where Flaggr leads
- Open-source (MIT) and self-hostable — Next.js control plane + Go data plane, Helm chart included
- Multi-protocol by design: REST, Connect-RPC, gRPC-Web, OFREP, and SSE streaming
- Built-in observability — OpenTelemetry traces, Prometheus metrics, Grafana dashboards, toggle-impact drift analysis, and circuit-breaker auto-rollback
- MCP server — AI agents can list, toggle, and evaluate flags natively
- Closed-loop delivery — canary pipelines with health gating, multi-armed bandits, cohort targeting
- Live public demo — a 4,096-flag pixel grid on flaggr.dev exercises the real API in front of you
Where Statsig fits better
Honest cases — we'd rather you pick the right tool.
- Experimentation rigor is the primary need — Statsig's stats engine is genuinely deeper
- You want flags + product analytics + experiments in one managed SaaS
- Statsig strengths: best-in-class experimentation engine — sequential testing, cuped, advanced stats
Common questions
Does Flaggr replace Statsig for experimentation?
Partially — Flaggr has experiments, multi-armed bandits, and toggle-impact analysis, which covers most flag-adjacent experimentation. Statsig's stats engine (CUPED, sequential testing) is deeper for dedicated experimentation programs.
Why pick Flaggr if Statsig has more experiment features?
Independence and cost. Flaggr is open-source and self-hostable — you're not paying event-volume pricing or locked into a proprietary SDK. For flag management itself, Flaggr's multi-protocol surface is broader.
Can I use Flaggr with my existing analytics?
Yes — Flaggr emits evaluation events and metrics you can pipe to any analytics stack. It doesn't assume it owns your analytics.
Try Flaggr in front of you
The landing-page pixel grid drives 4,096 real flags through the public API — or self-host the whole stack in minutes.
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