Deeplearning4j vs Horovod
Deeplearning4j
deeplearning4j.konduit.aiHorovod
horovod.aiSide by side
| Figure | Deeplearning4j | Horovod |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Deep Learning Software | 8.7 (#4) | 8.1 (#11) |
| Open source | The libraries are described as completely open source under the Apache 2.0 license and under Eclipse Foundation governance. | Horovod is described as an open source project hosted by the LF AI & Data Foundation. |
| Purpose | Eclipse Deeplearning4j is an open-source, distributed deep learning framework for the JVM. | Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch and Apache MXNet. |
| Spark | The documentation lists Apache Spark integration for distributed training. | Horovod can run on Apache Spark to combine data processing and model training in one pipeline. |
| Support | The support page lists GitHub issues, community forums, Stack Overflow, and professional support from Konduit. | The project directs users to documentation, troubleshooting guidance and a ticket submission link for unresolved issues. |
Plans
In their own words
Deeplearning4j
Deeplearning4j is an open-source framework for building, training, and deploying neural networks on the JVM, using Java or Scala. It can compute on CPUs through OpenBLAS and oneDNN, or use CUDA for GPU acceleration. For distributed training, it supports Apache Spark across CPU or GPU clusters. The framework can import models from Keras, TensorFlow, and ONNX, while Python4J provides Python interoperability from Java through CPython embedding. Its wider ecosystem includes ND4J, SameDiff, DataVec, Keras Import, Python4J, OmniHub, and Arbiter. Documented deployment targets include JVM microservices, mobile devices, IoT, and Spark environments. The libraries are licensed under Apache License 2.0 and governed by the Eclipse Foundation. The quickstart recommends Maven for Java projects, with Ivy and Gradle also workable. Documentation covers version 1.0.0-M2.1. The free plan is listed at free. Support options include GitHub issues, community forums, Stack Overflow, and professional support from Konduit.