Platform
Resources
Migrate from self-hosted GrowthBook to Statsig
Running a self-hosted experimentation platform sounds great in theory. You control the data, customize the setup, and avoid vendor lock-in. But after months of maintaining GrowthBook infrastructure, debugging deployment issues, and explaining to stakeholders why experiments take days to configure, many teams realize they're spending more time on tooling than actual product development.
The migration question isn't about abandoning open source principles—it's about choosing where to invest engineering resources. This analysis digs into the technical and operational differences between self-hosted GrowthBook and Statsig's managed platform, based on real migration experiences from companies processing billions of events daily.
Company backgrounds and platform overview
Statsig launched in 2020 when engineers from Facebook's experimentation team decided to build something better. They'd seen firsthand how companies struggled with legacy tools that couldn't handle modern scale. Their goal was clear: create the fastest experimentation platform that could process trillions of events daily.
GrowthBook emerged from different roots—frustration with expensive A/B testing platforms that locked away data. The founders wanted an open-source alternative that gave teams complete control. They built it MIT-licensed from day one, prioritizing transparency and community contribution. This philosophy attracts teams who want to own their entire stack.
These origins shaped fundamentally different approaches to experimentation infrastructure. Statsig focused on enterprise-grade infrastructure that could handle OpenAI's ChatGPT launches and Notion's 300+ quarterly experiments without breaking a sweat. GrowthBook emphasized self-hosting flexibility and data warehouse integration for teams wanting full ownership.
The warehouse-native story reveals how both platforms evolved. GrowthBook treats warehouse integration as core—you connect your existing data sources and run experiments there. Statsig provides dual deployment options: fully managed cloud infrastructure or warehouse-native for strict data requirements. This flexibility becomes crucial when migrating from self-hosted setups where data sovereignty matters.
Feature and capability deep dive
Experimentation capabilities
Statistical rigor separates professional experimentation platforms from glorified feature toggles. GrowthBook provides Bayesian and Frequentist engines with a visual editor for non-technical users—solid foundations for most use cases. But when you're running hundreds of experiments simultaneously, basic statistics aren't enough.
Statsig extends these capabilities with tools that matter at scale:
Sequential testing that lets you peek at results without inflating false positive rates
CUPED variance reduction that can cut experiment runtime by 50%
Automated heterogeneous effect detection that surfaces segment-specific impacts you'd miss otherwise
The infrastructure gap becomes obvious in production. Statsig processes experiments at 1 trillion events daily with sub-millisecond latency. GrowthBook's performance depends entirely on your infrastructure choices and optimization efforts. One Statsig customer migrating from self-hosted solutions reported reducing experiment setup time from days to hours.
Statistical sophistication reveals another key difference. While GrowthBook offers standard corrections, Statsig includes advanced techniques like stratified sampling for complex experimental designs and Bonferroni correction with Benjamini-Hochberg procedures. These aren't academic exercises—they're the difference between trustworthy results and statistical noise when running multiple experiments.
Platform integration and developer experience
Developer experience determines adoption speed. Both platforms provide 30+ SDKs across major programming languages, but implementation philosophy differs dramatically. GrowthBook requires careful orchestration between your feature flag service, analytics pipeline, and experimentation layer. Statsig bundles these components into a unified system.
The manual setup GrowthBook requires for analytics integration creates ongoing maintenance burden. You'll configure data sources, maintain ETL pipelines, and debug integration issues. Statsig's approach eliminates this complexity: experimentation, feature flags, analytics, and session replay share a unified data pipeline. One integration, multiple capabilities.
Edge computing support showcases architectural differences. Statsig includes edge SDKs and automatic rollback features when metrics breach thresholds. Self-hosted GrowthBook requires building these safety mechanisms yourself. As one Statsig user noted on G2: "Having feature flags and dynamic configuration in a single platform means that I can manage and deploy changes rapidly."
The migration path from self-hosted GrowthBook to Statsig typically involves three phases: SDK swapping (1-2 days), historical data migration (optional), and team training (1 week). Companies report the hardest part isn't technical—it's letting go of infrastructure management habits.
Pricing models and cost analysis
Pricing structure comparison
GrowthBook charges $20/user/month for Pro features with unlimited traffic and feature flags. Seat-based pricing creates predictable costs but punishes growing teams. A 50-person engineering org pays $1,000 monthly before considering infrastructure costs.
Statsig's usage-based model flips the equation. Pricing scales with analytics events, not headcount. Teams get unlimited seats and feature flags at every tier. The free tier covers 10M events monthly—enough for most mid-sized companies. This approach particularly benefits engineering-heavy organizations where everyone needs platform access.
Self-hosting economics tell a complex story. GrowthBook eliminates vendor costs but requires:
Database hosting and scaling
DevOps time for maintenance
Security patching and compliance work
Performance optimization as traffic grows
Statsig's cloud hosting handles these concerns automatically with 99.99% uptime. The warehouse-native option provides data control without operational overhead—a middle ground many migrating teams prefer.
Real-world cost scenarios
Let's examine actual migration economics. A 100-person team with 5M MAU running GrowthBook self-hosted might spend:
$2,000/month on infrastructure (compute, storage, networking)
40 hours/month of DevOps time ($8,000 value at $200/hour)
Additional costs for monitoring, backups, and security tools
The same team on Statsig would likely fall within the free tier or pay minimal usage fees. Even at scale, the comprehensive feature flag cost analysis shows Statsig offering unlimited free feature flags while competitors charge per flag or per user.
Enterprise features reveal hidden costs. GrowthBook charges extra for SSO, data pipelines, and approval workflows. Statsig includes warehouse-native deployment, advanced statistics, and enterprise security in standard pricing. This bundled approach eliminates budget surprises during scaling. SoundCloud's SVP Don Browning noted they "evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration."
Migration complexity and implementation considerations
Data architecture and deployment models
GrowthBook's self-hosted deployment gives you complete control—and complete responsibility. You'll manage database schemas, configure load balancers, and optimize query performance. This works for teams with strong DevOps capabilities and specific compliance requirements.
Migrating to Statsig doesn't mean abandoning data control. The platform offers three deployment models:
Fully managed cloud: Zero infrastructure overhead, fastest time to value
Warehouse-native: Your data stays in Snowflake/BigQuery/Databricks
Hybrid: Sensitive data stays local, metadata in Statsig cloud
Notion scaled from single-digit to 300+ experiments per quarter after migrating from their in-house solution. Their secret? Choosing managed infrastructure let them reassign four engineers from tooling to product development. As Wendy Jiao, Software Engineer at Notion, explained: "A single engineer now handles experimentation tooling that would have once required a team of four."
Support infrastructure and scalability
GrowthBook relies on community support for free tier users. Response times vary; complex issues might take days to resolve. Pro customers get email support, but you're still responsible for implementation details and infrastructure troubleshooting.
Statsig provides AI-powered support and dedicated customer data scientists across all tiers. More importantly, the platform's infrastructure scales automatically. OpenAI processes over 1 trillion events daily through Statsig without performance degradation. Self-hosted GrowthBook scalability depends entirely on your ability to optimize and scale infrastructure.
The human cost of self-hosting often gets overlooked. Your team spends time on:
Security patches and version upgrades
Performance debugging and optimization
Integration maintenance as APIs evolve
Training new team members on custom setups
These hidden costs compound over time. Teams migrating to Statsig report 50-70% reduction in experimentation overhead when factoring in all operational aspects.
Compliance and data governance
Both platforms support warehouse-native deployments for strict data governance. GrowthBook's self-hosted option keeps everything within your infrastructure by default. You control security configurations, audit logs, and compliance certifications—assuming you implement them correctly.
Statsig offers SOC 2 Type II and GDPR compliance out of the box. The warehouse-native deployment lets sensitive data remain in your Snowflake, BigQuery, or Databricks instance while leveraging Statsig's computation engine. Brex chose this approach to maintain data control while eliminating operational overhead.
Migration doesn't mean compromising on security. Statsig's enterprise features include:
Role-based access control with SSO integration
Audit logs for all configuration changes
Private cloud deployment options for maximum isolation
Data residency controls for geographic compliance
Why teams migrate from self-hosted GrowthBook to Statsig
The migration decision usually stems from three pain points. First, infrastructure maintenance consumes engineering time better spent on product development. Second, self-hosted solutions often lag in advanced features like automated analysis and real-time monitoring. Third, the total cost of ownership exceeds initial estimates once you factor in human resources.
GrowthBook serves its purpose for teams wanting complete control. But as organizations scale, the overhead becomes unsustainable. Statsig eliminates infrastructure burden while preserving flexibility through warehouse-native options. You get enterprise capabilities without the enterprise complexity.
The unified platform approach fundamentally changes how teams work. Instead of juggling separate tools for flags, experiments, and analytics, everything lives in one system. Brex's Head of Data, Sumeet Marwaha, captured this perfectly: "The biggest benefit is having experimentation, feature flags, and analytics in one unified platform. It removes complexity and accelerates decision-making."
Scale comes standard with Statsig, not as an expensive upgrade. The platform handles massive traffic spikes without manual intervention. Features like automatic rollbacks and real-time health monitoring protect production environments. Companies like OpenAI, Figma, and Bluesky trust this infrastructure for their growth trajectories.
The financial case becomes clearer over time. Beyond GrowthBook's per-seat pricing, consider the fully loaded costs: infrastructure, maintenance, opportunity cost of engineering time. Statsig's model—with unlimited free feature flags and usage-based pricing—typically reduces total experimentation costs by 50% or more. The most affordable experimentation platform becomes even more valuable when you factor in faster experiment velocity and reduced time-to-insight.
Closing thoughts
Migrating from self-hosted GrowthBook to Statsig isn't about abandoning open source or losing control. It's about choosing where to invest engineering effort. The teams who make this transition successfully focus on their core product instead of maintaining experimentation infrastructure.
The path forward depends on your specific constraints. If regulatory requirements demand complete on-premises deployment, self-hosting remains necessary. But for most teams, Statsig's combination of managed infrastructure, warehouse-native options, and enterprise features provides the best of both worlds: control where it matters, convenience everywhere else.
Ready to explore migration options? Check out Statsig's migration guide or dive into their technical documentation to understand implementation details. For teams currently evaluating options, the interactive ROI calculator helps quantify the real costs of different approaches.
Hope you find this useful!