Singa
Distributed training of DL and ML models for Apache.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
UnverifiedOverview
What is Singa?
Apache Singa is a distributed deep learning platform designed to train large-scale machine learning models efficiently across multiple machines. It supports various neural network architectures and offers flexibility in model deployment.
Key differentiator
“Singa stands out as an open-source, Apache-licensed platform specifically designed for the efficient and scalable distributed training of deep learning models.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official documentation and community resources are sparse for languages other than C++ and Python
Few active contributors and less third-party tooling compared to more popular platforms like TensorFlow or PyTorch
Fit analysis
Who is it 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
✕ Not a fit for
Projects with small datasets that do not require distributed training
Developers looking for a cloud-based managed service solution
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with Singa
Step-by-step setup guide with code examples and common gotchas.