Featurevisor vs GrowthBook
Featurevisor
featurevisor.com
GrowthBook
growthbook.ioSide by side
| Figure | Featurevisor | GrowthBook |
|---|---|---|
| Price from | Free | $40/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| iOS | Yes | Yes |
| Android | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 9 |
| Spec score · Feature Flag Software | 8.7 (#7) | 9.0 (#5) |
| Deployment | Datafiles are served from the customer’s own CDN, with no vendor in the request path. | GrowthBook is available as a managed cloud service or self-hosted, including air-gapped deployment on major clouds or on-premises. |
| Documentation depth | The documentation covers concepts, quick start, attributes, segments, features, variables, targets, projects, configuration, linting, building, testing, deployment and SDKs. | The docs include quickstart, API, webhooks, integrations, security, self-hosting, SDK, tutorials and agent guides. |
| Feature flags | Boolean flags use ordered targeting rules whose first matching rule determines the result. | Feature flags support targeting, gradual rollouts, low-latency delivery and rollback control. |
| Founded | The project’s first public v0.1 announcement is dated March 5, 2023. | 2020 |
| What it does | Featurevisor manages feature flags, experiments and remote configuration as files in Git, then builds datafiles consumed by SDKs. | GrowthBook combines warehouse-native experimentation, feature flags and product analytics for controlled releases and A/B testing. |
Plans
GrowthBook
- Open SourceFree
- Open Source (Self-Hosted)Free
- StarterFree
- Starter (Cloud)Free
- Pro$40 a month
- Pro (Cloud)$40 a month
- EnterprisePriced on request
- Enterprise (Cloud)Priced on request
- Enterprise (Self-Hosted)Priced on request
In their own words
Featurevisor
Featurevisor is a Git-based tool for managing feature flags, experiments and remote configuration through YAML files in a Git repository. Teams build datafiles for each environment, deploy them and evaluate features through an SDK. Rules can target users in order, roll out a percentage and assign weighted experiment variations. Typed global and feature variables allow defaults and targeted overrides, with schemas validated during datafile builds. Applications fetch static JSON datafiles and evaluate flags locally in memory, without a network request for each decision; the datafiles are served from the customer’s own CDN. YAML test specifications can check expected behavior locally or in CI, with failed assertions returning a non-zero exit. Git pull requests and CI linting, tests and builds provide change control. Featurevisor is self-hosted and MIT-licensed. Its free plan is free, with no per-seat pricing or evaluation service to keep running. Listed platforms include Android, iOS, Linux, macOS, web and Windows.
GrowthBook
GrowthBook has no write-up on Specifiction yet; its figures are above.