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GrowthBook
Open-source feature flagging and A/B testing platform.
What it does
Manages fine-grained feature flags and controlled code rollouts across applications. Runs advanced A/B tests using an organization's existing data warehouse metrics. Analyzes product usage trends and user behavior through integrated product analytics. Provides flexible statistical engines supporting both frequentist and Bayesian models.
Why it works
Operates on an open-source, warehouse-native architecture that protects data privacy and security. Avoids external data storage costs by connecting directly to existing cloud data warehouses. Offers a freemium and tiered subscription model scaling seamlessly for growing organizations. Provides lightweight SDKs that integrate smoothly into modern software tech stacks.
Category: Marketing & Growth
Team Size: 26-100
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As of 2026
Marketing & Growth
Revenue: $1M-$10M ARR
Open-source feature flagging and A/B testing platform.
Overview
GrowthBook is an open-source, warehouse-native platform that combines feature flagging, A/B testing, and product analytics. It enables product and engineering teams to run experiments and manage feature rollouts directly on top of their existing data infrastructure. By keeping data secure within company data warehouses, it eliminates third-party vendor lock-in and high cloud costs. The platform serves thousands of modern tech companies worldwide.
Funding status: Funded
Revenue source: Subscriptions
Customer type: B2B
Pricing: Freemium
Tech stack: TypeScript, React, Node.js, Go
Platform: Web
Integrations: Snowflake, BigQuery, Redshift, PostgreSQL, Mixpanel
Founder story
GrowthBook was founded in 2020 by Graham McNicoll and Jeremy Dorn in San Francisco, California. Having previously scaled software systems together at Education.com, the founders set out to eliminate the frustrations of traditional closed experimentation tools. They built GrowthBook to give product teams transparent, flexible, and warehouse-connected tools for data-driven iteration.
What it does
- Manages fine-grained feature flags and controlled code rollouts across applications
- Runs advanced A/B tests using an organization's existing data warehouse metrics
- Analyzes product usage trends and user behavior through integrated product analytics
- Provides flexible statistical engines supporting both frequentist and Bayesian models.
Who it's for
- Product Managers
- Software Engineers
- Data Scientists
- Growth Marketers
Why it works
- Operates on an open-source, warehouse-native architecture that protects data privacy and security
- Avoids external data storage costs by connecting directly to existing cloud data warehouses
- Offers a freemium and tiered subscription model scaling seamlessly for growing organizations
- Provides lightweight SDKs that integrate smoothly into modern software tech stacks.
Growth strategies
- Open- source community adoption and developer-led grassroots distribution
- Strategic Y Combinator network backing and venture capital partnerships
- Content marketing focused on data- driven product management and warehouse-native benefits
- Self- serve cloud signups alongside enterprise-grade custom deployments
Alternatives
Comparison overview
- GrowthBook is warehouse-native and open-source, allowing companies to keep experimentation data within their own infrastructure, whereas legacy tools like LaunchDarkly require sending all user data to third-party cloud servers.
- GrowthBook allows custom SQL metric definitions inside data warehouses, contrasting with closed SaaS tools that restrict metrics to proprietary tracking loops.