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...Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications. Make your changes and simply hit refresh! All you need is a browser and a text editor. Underneath the covers Play uses a fully asynchronous model built on top of Akka.

...Finatra at its core is agnostic to the type of service or application being created. It can be used to build anything based on TwitterUtil: c.t.app.App. For servers, Finatra builds on top of the features of TwitterServer (and Finagle) by allowing you to easily define a Server and controllers (a Service-like abstraction) which define and handle endpoints of the Server. You can also compose Filters either per controller, per route in a controller, or across all controllers. Powerful Feature and Integration test support. ...

Lift is the most powerful, most secure web framework available today. There are Seven Things that distinguish Lift from other web frameworks. Lift apps are resistant to common vulnerabilities including many of the OWASP Top 10. Lift apps are fast to build, concise and easy to maintain. Lift apps are high-performance and scale in the real world to handle insane traffic levels. Lift's Comet support is unparalled and Lift's ajax support is super-easy and very secure. Because Lift applications are written in Scala, an elegant JVM language, you can still use your favorite Java libraries and deploy to your favorite Servlet Container and app server. ...

Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.