GrowthBook vs Statsig

GrowthBook is the open source leader in feature flagging and experimentation. Companies choose GrowthBook over Statsig for platform flexiblity, world-class feature flags, and cost-effective pricing at scale.

Comparison

At a glance: GrowthBook vs Statsig

Open source feature flag and experimentation leader trusted by 2,700+ companies with 7,000+ GitHub stars
Warehouse-native architecture with full SQL visibility for maximum control, flexibility, and no vendor lock-in
Per-seat pricing is more predictable and cost-effective than event-based pricing
Proprietary feature management and experimentation platform
OpenAI acquisition introduces uncertainty around data privacy, the product roadmap, and the long-term viability of the product
Expensive, event-based pricing can result in unexpected cost spikes

Why choose GrowthBook over Statsig

Designed for
Primary Use
Statistical Methods
Deployment Options
Pricing & Plans
Setup Time
growthbook logo

Developer-friendly, full-stack
experimentation platform

Designed for
Developers, product teams, analysts
Primary Use
Test any new feature you build in any platform
Statistical Methods
Bayesian, frequentist, sequential (with CUPED, post-stratification)
Deployment Options
Cloud or fully self-hosted
Pricing & Plans
Per-seat pricing with unlimited tests, unlimited traffic
Setup Time
Hours
Statsig

Proprietary experimentation
platform

Designed for
Product and engineering teams
Primary Use
Run experiments and feature flags 
Statistical Methods
Bayesian, frequentist, sequential (with CUPED)
Deployment Options
Cloud-hosted, partially warehouse native option
Pricing & Plans
Usage-based pricing tied to events and traffic
Setup Time
Days to weeks

Ready to migrate from Statsig to GrowthBook?

When costs limit experimentation at scale, it’s time to switch to GrowthBook.

How GrowthBook compares to Statsig?

Statsig customers switch to GrowthBook for trusted experiments, predictable costs, and better control over their stack.

Developer-friendly, intuitive environment for fast iteration
Developer-friendly, intuitive environment for fast iteration
Clear documentation, AI chatbot access, and responsive support
Clear documentation, AI chatbot access, and responsive support
Powerful platform with a steep learning curve for non-technical users
Requires careful setup and instrumentation to ensure reliable results
No visual editor
Run any number of experiments on any amount of traffic
Low-latency SDKs with rapid rule processing
Low-latency SDKs with rapid rule processing
99.999% uptime for high traffic websites and apps
Costs scale with events and traffic, limiting experimentation and flagging
Costs scale with events and traffic, limiting experimentation and flagging
Platform performance depends on hosted infrastructure
Testing types: Supports A/B tests, multivariate tests, redirects, visual editor, and holdouts
Full-stack coverage: server-side, client-side, mobile, and edge experiments
Flexible targeting and randomization units user, location, postal code, URL path, etc.
Statistical frameworks: Bayesian, frequentist, sequential (with CUPED, post-stratification)
Full-stack experimentation and feature rollouts
Limited visibility into analytics and SQL
Bayesian, frequentist, sequential (with CUPED)
World-class feature flags at the core
Controlled rollouts, gradual exposure, and instant kill switches
Zero network call SDKs for low latency and high reliability
Zero network call SDKs for low latency and high reliability
Feature flags cannot be converted to experiments retroactively
With event-based pricing, every feature flag check counts as a billable event
Bring your data architecture Snowflake, BigQuery, Redshift, Postgres, etc.
Analyze all your product and experimentation data in one place
Reproduce and confirm any GrowthBook calculation
Customize metrics using SQL, use metric libraries, and even add metrics retroactively
Warehouse-native capability added, creating 2 code bases
Proprietary stats engine that cannot be inspected or audited
Not open source
Limited ability to reproduce or audit platform calculations
Fully self-hosted, air-gapped option for data residency requirements
Meets strict privacy compliance requirements GDPR, HIPAA, CCPA, SOC 2 Type II certified
No end-user PII required. Your data stays in your data warehouse
Open-source code is publicly available for security review on GitHub
No self-hosted deployment
All event data flows through Statsig servers (now owned by OpenAI)
No published policy on data firewall from OpenAI AI training
3 of the 5 leading AI companies use GrowthBook to optimize their chatbots and APIs
3 of the 5 leading AI companies use GrowthBook to optimize their chatbots and APIs
3 of the 5 leading AI companies use GrowthBook to optimize their chatbots and APIs
MCP integration for natural language access to GrowthBook in IDE (Claude Code, Cursor, VS Code, etc.)
AI evaluation and model experimentation tools
Customization limited to Statsig’s evaluation framework
Platform roadmap and priorities now influenced by OpenAI
Predictable per-seat pricing with unlimited experiments and unlimited traffic
Free tier and open source options
Enterprise self-hosting gives customers flexibility and control
Warehouse-native architecture means you do not pay twice to capture the same data
Usage-based pricing on both experiments and feature flag events
Costs often spike after vendor lock in
Requires ongoing monitoring to manage spend at high volume
Engineering-led implementation often requires more resources

“We don’t need any code changes, we don’t need an app release. We just configure the new tests and launch right away.”

Filipa Batista
Product Manager, Lingokids

“Our goal was to consolidate everything into a single platform while saving money and ensuring compliance and security.”

Alex Kalish
Engineering Manager, Dropbox

“Being able to turn a feature on and off with a flip of a switch 
is fantastic... That’s so much easier than having to do a deploy or a roll-back.”

John Resig
Chief Software Architect, Khan Academy

“Experimentation showed what customers actually do rather than what we assume they’ll do.”

Marek Maciusowicz
Head of Engineering, Treatwell

“People only see the wins, but there’s actually greater value in avoiding losses. We’ve stopped changes that could have cost millions.”

Merritt Aho
Digital Analytics Lead at Breeze Airways

"GrowthBook allowed us to uplevel our code, speed up decision-making, and focus on what we do best—building a world-class AI lending marketplace."

Diego Accame
Director of Engineering, Growth at Upstart

"The fact that we could retain ownership of our data was very, very important. Almost no solutions out there allow you to do that."

John Resig
Chief Software Architect, Khan Academy

“GrowthBook lets us build experiments exactly how we want. The ability to target based on culture and geography, as granular as needed, is a major win for us.”

Eslam Samy
Data Scientist, Floward

"The fact that GrowthBook offered us the ability to keep that data in-house was a key reason why we chose to work with them."

Diego Accame
Director of Engineering, Growth at Upstart

"The fact that GrowthBook offered us the ability to keep that data in-house was a key reason why we chose to work with them."

Diego Accame
Director of Engineering, Growth at Upstart

"The fact that we could retain ownership of our data was very, very important. Almost no solutions out there allow you to do that."

John Resig
Chief Software Architect, Khan Academy

“GrowthBook lets us build experiments exactly how we want. The ability to target based on culture and geography, as granular as needed, is a major win for us.”

Eslam Samy
Data Scientist, Floward

More comparisons

FAQs

Yes. GrowthBook supports full self-hosting, giving teams complete control over their data and infrastructure. Statsig is cloud-only with no self-hosted deployment option.

The OpenAI acquisition of Statsig introduces new risks around platform longevity and data governance. Statsig’s CEO has since left, and the product is now part of OpenAI’s platform portfolio, where acquisitions have a risk of being discontinued. There is also no published policy separating customer experimentation data from OpenAI’s AI training. GrowthBook remains independent and open-source, giving teams more long-term control over their experimentation infrastructure.

A proprietary experimentation engine means your team cannot inspect statistical calculations, reproduce results, or audit experiment logic. An open source engine makes all of that possible in your own environment. Statsig's engine is proprietary, whereas GrowthBook's is fully open source, so your data team can inspect every query and validate any outcome.

GrowthBook offers more predictable pricing for experimentation than Statsig. GrowthBook' per seat pricing with unlimited experiments and feature flags is more predictable. Statsig usage-based pricing is based on metered events. Cost increases as experiments, and feature flags, scale.

Yes, both have proven capability to handle billions of event look ups. The difference is in the pricing - with GrowthBook you have predictable per seat pricing with unlimited feature flags and experiments, whereas Statsig costs can spike with traffic. Companies often reduce the amount of traffic they test on to contain costs.

GrowthBook is open source with full SQL visibility and tranparency. Statsig is a proprietary platform owned by OpenAI. GrowthBook lets teams inspect experiment logic, run analysis in their own warehouse, and self-host if needed

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