Replace GrowthBook feature flags with Statsig

Choosing between experimentation platforms isn't just about features - it's about finding the right balance between control and convenience. GrowthBook gives you an open-source foundation with complete data ownership, while Statsig delivers enterprise-grade capabilities without the infrastructure headaches.

The real question is whether you want to build and maintain your own experimentation infrastructure or focus on running experiments. This comparison digs into the technical trade-offs, pricing realities, and operational differences that matter when your team needs to ship faster and learn quicker.

Company backgrounds and platform overview

Statsig launched in 2020 when ex-Facebook engineers built an experimentation platform without legacy constraints. They created four integrated tools: experimentation, feature flags, analytics, and session replay. Today, Statsig processes over 1 trillion events daily for companies like OpenAI, Notion, and Figma.

GrowthBook emerged as an open-source A/B testing alternative to expensive commercial platforms. Its creator wanted to avoid sending sensitive data to third parties like Optimizely. The platform integrates with existing analytics tools - Snowplow, Segment, Mixpanel - without adding performance-heavy script tags.

Both platforms serve different philosophies. GrowthBook champions open-source flexibility and self-hosted control for privacy-conscious teams. Statsig focuses on enterprise scale with both cloud and warehouse-native deployments. The distinction matters because it shapes everything from implementation complexity to long-term costs.

GrowthBook's approach appeals to teams wanting complete data ownership. You can self-host the platform and maintain full control over your infrastructure. The platform queries existing data sources rather than collecting new events, which sounds great until you realize you're responsible for scaling, maintaining, and updating everything yourself.

Statsig built for massive scale from day one. Their infrastructure handles billions of users across thousands of experiments. Companies choose between hosted cloud or warehouse-native deployments based on their data governance needs. As Paul Ellwood from OpenAI puts it: "Statsig's infrastructure and experimentation workflows have been crucial in helping us scale to hundreds of experiments across hundreds of millions of users."

Feature and capability deep dive

Experimentation capabilities

Modern experimentation demands more than basic A/B testing. Statsig delivers CUPED variance reduction, sequential testing, and automated heterogeneous effect detection - features rarely found in open-source alternatives. These techniques reduce experiment runtime by 30-50% while maintaining statistical rigor.

GrowthBook provides both Bayesian and Frequentist engines, covering most standard use cases. But it lacks enterprise features like automated rollback triggers and interaction effect detection. You'll need to build these capabilities yourself or monitor experiments manually.

The difference becomes clear at scale. When you're running hundreds of experiments:

• Statsig automatically detects metric regressions and rolls back harmful changes

• GrowthBook requires manual monitoring or custom alerting infrastructure

• Statsig identifies user segments with different treatment effects automatically

• GrowthBook needs manual segment analysis

For teams running just a few experiments monthly, manual monitoring might work. But once you hit 50+ concurrent experiments, that operational overhead becomes a full-time job.

Developer experience and integrations

Both platforms offer 30+ SDKs across major languages and frameworks. Statsig's edge computing support delivers sub-millisecond evaluation latency - critical for performance-sensitive applications. GrowthBook's SDKs perform well but lack edge deployment options.

The real differentiation lies in platform integration. Statsig includes built-in session replay and unified analytics, creating a complete product development toolkit. GrowthBook focuses solely on experimentation and feature flags; you'll need separate tools for user analytics and session recording. One Statsig user noted: "Implementing on our CDN edge and in our nextjs app was straight-forward and seamless."

This integration gap affects daily workflows dramatically. With Statsig, you can:

• Watch actual user sessions from experiment variants

• Analyze conversion funnels without switching tools

• Debug feature flag issues with real session context

• Track custom metrics alongside experiment results

GrowthBook users switch between multiple tools, losing context and efficiency. For resource-constrained teams, this difference determines whether experimentation becomes a core practice or remains an occasional activity.

Pricing models and cost analysis

Pricing structure comparison

GrowthBook charges $20 per user monthly for Pro features, with enterprise plans requiring custom negotiations. SSO integration costs extra. The free tier caps at three users. This per-seat model means costs scale linearly with team size - a painful reality for growing companies.

Statsig provides unlimited users and feature flags free forever. You pay only for analytics events with transparent volume-based discounts. No hidden SKUs or surprise charges. Just straightforward usage-based pricing that scales with your actual product usage, not your headcount.

Real-world cost scenarios

Let's talk real numbers:

• 50-person team running 100 experiments monthly: $1,000+ on GrowthBook Pro

• Same team on Statsig: Potentially $0 on the generous free tier

• 200 engineers on GrowthBook: $4,000 monthly before enterprise features

• 200 engineers on Statsig: $0 for seats - you pay only for event volume

Enterprise deployments see 50%+ savings with Statsig due to no per-seat charges. Bundled analytics eliminates separate tool costs. One customer evaluation revealed: "We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one."

The math becomes clearer at scale. Seat-based pricing punishes team growth. Event-based pricing rewards efficiency. This fundamental difference compounds as teams grow and experiment velocity increases.

Decision factors and implementation considerations

Implementation complexity

GrowthBook's self-hosted option requires significant DevOps investment. You'll need to:

• Manage database connections and scaling

• Configure analytics pipeline integrations

• Handle server maintenance and security updates

• Plan for traffic spikes and data growth

This works for teams with existing infrastructure expertise and dedicated DevOps resources. But it's a distraction for product teams trying to ship features quickly.

Statsig offers turnkey cloud deployment or warehouse-native options, both with managed infrastructure handling trillions of events seamlessly. Setup takes minutes rather than days. Your team focuses on experiments instead of infrastructure management - exactly where they add the most value.

Support and community resources

GrowthBook relies heavily on community support through Slack, with paid plans receiving priority assistance from a smaller team. The 4,500+ member community provides peer support for common issues. Response times vary based on community availability and plan level.

Statsig provides dedicated customer success managers, data scientists for experiment design, and direct access to engineering teams. Enterprise customers work directly with technical experts who understand their specific use cases. This hands-on support model helps teams launch sophisticated experiments faster. As Sumeet Marwaha from Brex notes: "Our engineers are significantly happier using Statsig. They no longer deal with uncertainty and debugging frustrations."

The support difference matters most during critical moments: botched deployments, unexpected metric movements, or complex statistical questions. Having experts on call beats posting in community forums and hoping for timely responses.

Data ownership and privacy considerations

Both platforms support warehouse-native deployments for teams with strict data governance requirements. GrowthBook connects to your existing data sources without storing raw events. Statsig's warehouse-native option processes all calculations within your infrastructure - no data leaves your environment.

The key difference lies in flexibility. Statsig offers both hosted and warehouse-native options within the same platform. You can start with hosted deployment and migrate to warehouse-native later without switching tools. This dual approach accommodates changing privacy requirements as your company grows.

For most teams, the hosted option provides sufficient security with SOC 2 compliance and enterprise-grade encryption. But having the warehouse-native escape hatch means you're never locked into a deployment model that might not fit future requirements.

Bottom line: why Statsig beats GrowthBook for most teams

While GrowthBook offers a solid open-source foundation, Statsig eliminates the infrastructure burden that comes with self-hosting. You get enterprise-grade capabilities without managing servers, updates, or scaling challenges. For teams needing data control, Statsig's warehouse-native deployment provides the same privacy benefits alongside its hosted option.

The integrated platform sets Statsig apart from GrowthBook's modular approach. Instead of piecing together separate tools, you get experimentation, feature flags, analytics, and session replay in one system. This unified approach means consistent metrics, shared user segments, and seamless workflows across your entire product development cycle.

Proven scale matters when your product grows. Statsig processes over 1 trillion events daily and serves billions of users for companies like OpenAI and Notion. GrowthBook's self-hosted model puts scaling responsibilities on your team. With Statsig, you get 99.99% uptime and sub-millisecond latency without the operational overhead.

Cost efficiency becomes critical at scale. Statsig's transparent pricing typically runs 50% cheaper than alternatives, with unlimited feature flags at every tier. Unlike GrowthBook's seat-based pricing, Statsig charges only for analytics events - not users, flags, or experiments.

Sumeet Marwaha from Brex summarizes it well: "The biggest benefit is having experimentation, feature flags, and analytics in one unified platform. It removes complexity and accelerates decision-making by enabling teams to quickly and deeply gather and act on insights without switching tools."

Closing thoughts

Choosing an experimentation platform shapes how your team builds products. GrowthBook works for teams with strong DevOps capabilities and specific self-hosting requirements. But for most organizations, Statsig's combination of power, simplicity, and cost-effectiveness makes migration a straightforward decision.

The real value comes from removing friction between ideas and insights. When your platform handles the complexity, your team can focus on what matters: running experiments, learning from users, and shipping better products.

For a deeper dive into migration strategies and technical comparisons, check out Statsig's migration guides and pricing calculator. Hope you find this useful!