Open source alternatives to Statsig

What Statsig does

Statsig is a hosted platform built around experimentation. Teams run A/B tests through feature gates and experiments, and a statistics engine reports the results with Bayesian or frequentist methods, variance reduction using historical data, corrections for multiple comparisons, holdouts and multi-arm bandits. Dynamic config serves JSON values that can change without a deploy. Product analytics, session replay and web analytics sit alongside, linked to the same flags and metrics. Enterprise customers can run Statsig in warehouse-native mode on their own data warehouse instead of sending events to Statsig’s cloud.

Why people look for an alternative

• Ownership changes. Statsig signed an agreement to join OpenAI in September 2025. On 5 May 2026 Amplitude took over the Statsig product, brand and customers, while the original team stayed at OpenAI. Amplitude says it will keep developing Statsig and connect it with Amplitude’s own products. Some customers prefer a tool whose future does not depend on a vendor’s plans.
• Event-based pricing. Paid plans include a quota of events and charge for more, and Enterprise contracts are based on events or experiments, so cost rises with traffic.
• Where the data goes. In the standard cloud mode, exposures and events are processed by Statsig. Keeping data in your own warehouse requires the Enterprise plan.
• Access control on the top plan. SSO, role-based access control and teams are Enterprise features.
• Lock-in. Experiments, metrics and gates are defined in Statsig’s console, and application code calls Statsig’s SDKs.

What to compare in an alternative

1. Statistics. Bayesian or frequentist analysis, sample ratio mismatch checks, sequential testing and variance reduction, and which of these the open source edition includes.
2. Where analysis runs. On your own warehouse, inside the tool’s own database, or not at all (traffic splitting only).
3. Metrics source. Whether you need a data warehouse, or the tool collects events itself.
4. Flag features. Targeting, rollouts, remote config and local evaluation in SDKs.
5. Migration. GrowthBook documents an importer for Statsig features and experiments, and a guide for moving SDK calls.

Which one to choose

GrowthBook is the closest match. Like Statsig’s warehouse-native mode, it computes experiment results from SQL run against your own warehouse, with Bayesian and frequentist engines, and it can import Statsig features and experiments. Its open source edition is limited to one project, and some advanced statistics such as sequential testing, CUPED and bandits are commercial.

Bucketeer suits teams without a warehouse: it collects goal events itself and analyzes experiments with Bayesian statistics, with every feature under Apache-2.0, at the cost of a heavier deployment. FeatBit also offers Bayesian experiments with guardrail metrics on top of a self-hosted flag platform.

If you used Statsig as much for product analytics and session replay as for experiments, PostHog combines all three. For flags without built-in experiment statistics, see the full feature flag category.