feat vs Featurevisor
feat
feat.soFeaturevisor
featurevisor.comSide by side
| Figure | feat | Featurevisor |
|---|---|---|
| Price from | $19/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| iOS | Yes | Yes |
| Android | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 6 | 2 |
| Spec score · Feature Flag Software | 9.3 (#2) | 8.7 (#7) |
| Evaluation | Server SDKs evaluate locally in process, so flag reads do not make a network request. | Applications fetch static JSON datafiles and evaluate flags locally in memory without a network request for each decision. |
| Experiments | A built-in statistical engine, variant tracking, metric integrations, and auto-advance gradual rollouts are listed as coming in Q3 2026. | Features can define weighted string variations for A/B and multivariate experiments. |
| Feature flags | Flags support boolean, string, number, and JSON values. | Boolean flags use ordered targeting rules whose first matching rule determines the result. |
| Percentage rollouts | Rollouts use stable bucketing so the same context keeps the same variation while weights remain unchanged. | Rules support percentage allocation for gradual rollouts using deterministic bucketing. |
| Segments | Reusable named segments can be referenced by multiple flags. | Reusable segments group users through conditions on declared runtime attributes. |
| What it does | feat is a hosted feature-flag platform for engineering and product teams. | Featurevisor manages feature flags, experiments and remote configuration as files in Git, then builds datafiles consumed by SDKs. |
Plans
feat
- FreeFree
- Starter$19 a month
- Growth$49 a month
- Scale$149 a month
- Elastic$299 a month
- EnterprisePriced on request
In their own words
feat
feat is a hosted feature-flag platform for early engineering teams. Server SDKs evaluate flags locally, so each flag read does not require a network call; changes stream to connected SDKs in under a second. Targeting rules combine conditions across users, devices, organizations, sessions, and requests using AND and OR. Sticky percentage rollouts keep a user, device, or organization on the same variation across requests and sessions. First-party SDKs are available for Node.js, Bun, Deno, Go, Python, Ruby, browser JavaScript, and Flutter/Dart, with OpenFeature providers for web, Node.js, and Dart. Metric sources include Segment, Mixpanel, PostHog, and custom sources. The Free plan costs nothing and includes 7,500 MAU, 100 server connections, two projects, unlimited environments, and unlimited flags. Starter costs $19 a month, with annual billing listed at $15/mo. Built-in statistical experiments, variant tracking, metric integrations, auto-advance gradual rollouts, and Slack integration are listed as coming in Q3 2026, not current features.
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.