Airship vs LaunchDarkly vs Split
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Serving over 200 billion feature flags daily to help software teams build better software, faster. LaunchDarkly helps eliminate risk for developers and operations teams from the software development cycle. | Feature flags as a service for data-driven teams: Split automatically tracks changes to key metrics during every feature rollout. Split serves billions of impressions, helping organizations of all sizes to rapidly turn ideas into products. | Airship is a modern product flagging framework that gives the right people total control over what your customers see & experience - without deploying code. |
Create custom environments;Team management;Create goals;Target or exclude user segments;New Relic integration;Optimizely integration;Audit logging;Custom roles and permissions | Targeted Feature Release - Easily target any feature, anywhere in the stack, to the right users based on any attribute you have access to, from demographic data to in-the-browser metrics;
Foster a culture of continuous improvement: Analyze the impact of every feature on hundreds of business, product, and operational metrics in real time;
Rigorous statistical analysis:
Split’s statistics engine provides causal analysis and guards against misleading results;
Easy-to-use Web Console - Split's UI gives anyone on the team the power to target feature releases, ramp up features to your customers, and instantly kill problem features | Launch control; Easy experimentation; Customer configurations; Testing & QA; Accelerate CI/CD; Trial campaigns |
Statistics | ||
Stacks 322 | Stacks 119 | Stacks 15 |
Followers 309 | Followers 121 | Followers 39 |
Votes 6 | Votes 2 | Votes 6 |
Pros & Cons | ||
Pros
| Pros
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Integrations | ||
| No integrations available | ||
What are some alternatives to LaunchDarkly, Split, Airship?
ConfigCat
Cross-platform feature flag service for Teams. It is a hosted or on-premise service with a web app for feature management, and SDKs for all major programming languages and technologies.
Unleash Hosted
It is a simple feature management system. It gives you great overview of all feature toggles across all your applications. You decide who is exposed to which feature.
Flagr
Open-source Go microservice supports feature flagging, A/B testing, and dynamic configuration. Logs data records and impressions.
Flagsmith
It lets you manage features flags and remote config across web, mobile and server side applications. Use our hosted API, deploy to your own private cloud, or run on-premises.
Rollout
Advanced feature flag solution that lets your dev teams quickly build & deploy applications without compromising on safety. A simple way to define target audiences allows devs & PMs optimize feature releases and customize user experience
Optimizely Full Stack
It is an experimentation and feature flagging platform for websites, mobile apps, chatbots, APIs, smart devices, and anything else with a network connection. You can deploy code behind feature flags, experiment with A/B tests, and rollout or rollback features immediately. All of this functionality is available with zero performance impact via easy-to-use SDKs.
FF4J
It is an implementation of Feature Toggle pattern : Enable and disable features or your applications at runtime thanks to dedicated web console, REST API, JMX or even CLI. It handle also properties and provide generic interfaces.
Bullet Train
Manage feature flags across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features.
Optimizely Rollouts
It is unlimited free feature flags and rollouts built on an enterprise-grade platform. Manage your features remotely and roll them out gradually to targeted audiences, without re-deploying your code. Connect Rollouts with Jira and invite your product and engineering teams to work together.
Flagship.io
Flagship.io is a feature flagging platform for modern engineering and product teams that eliminates the risks of future releases by separating code deployments from these releases.
