Clojure vs. Deeplearning4j vs. MXNet vs. VelocityDB Comparison Chart

Clojure is a robust, practical, and fast programming language with a set of useful features that together form a simple, coherent, and powerful tool. Clojure is a dynamic, general-purpose programming language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language, yet remains completely dynamic, every feature supported by Clojure is supported at runtime. Clojure provides easy access to the Java frameworks, with optional type hints and type inference, to ensure that calls to Java can avoid reflection. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system. Clojure is predominantly a functional programming language and features a rich set of immutable, persistent data structures. When a mutable state is needed, Clojure offers a software transactional memory system and reactive Agent system.

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.