Azure Databricks vs. Deeplearning4j vs. Java vs. seenode Comparison Chart

DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers.

seenode is the European developer cloud that makes deploying and running apps effortless. Whether you’re building with Django, Node.js, Python, or Elixir, Seenode provides an environment optimized for modern development workflows. Key features include Git-based deployments, CLI and API tooling, persistent storage, and worker services for background tasks. With pricing starting at just €3/month and a free 7-day trial, seenode offers an affordable alternative to platforms like Heroku or Railway -without vendor lock-in. By hosting entirely in the EU, seenode ensures fast performance, data compliance, and peace of mind for developers and businesses. Deploy your apps in minutes, manage them with ease, and scale without surprises.