Singa vs Horovod

Side-by-side — pricing, strengths, tradeoffs, and fit.

Singa

Distributed training of DL and ML models for Apache.

Horovod

Distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet.

At a glance

Open SourceFree Tier
· Not enough data·From $0
Open SourceFree Tier
◌ Declining·From $0

Overview

One-liner

Distributed training of DL and ML models for Apache.

One-liner

Distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet.

Maturity

Not enough data

Maturity

Declining

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Teams that need to train large-scale ML models across multiple machines
Organizations requiring flexible deployment options for their deep learning projects

✓ Best for

Teams that need to scale up their deep learning training across multiple GPUs or machines without significant code changes.
Developers working with TensorFlow, Keras, PyTorch, and Apache MXNet who want to leverage distributed computing for faster model training.

Not ideal for

✕ Not for

Projects with small datasets that do not require distributed training
Developers looking for a cloud-based managed service solution

✕ Not for

Projects requiring real-time inference as Horovod is focused on training rather than deployment
Small-scale projects where the overhead of setting up a distributed environment outweighs the benefits

Strengths

↑ Strengths

Supports distributed training across multiple machines
Flexible model deployment options
Scalable architecture for large-scale ML models

↑ Strengths

Support for multiple deep learning frameworks
Easy integration with existing training code
Scalability across multiple GPUs and machines
Compatibility with popular distributed computing systems like MPI

Weaknesses

↓ Weaknesses

Limited language support primarily focusing on C++ and Python
Small community and limited third-party integrations

↓ Weaknesses

Limited support for non-GPU environments
Complex setup and configuration
Full Singa profile →Full Horovod profile →