Database · ai-tools
Ray
An open-source distributed computing framework for scaling AI and machine-learning workloads across accelerators.
Open-source distributed computing framework
Overview
A current open-source option for readers comparing infrastructure used to scale AI and machine-learning workloads.
Details
- Website
- https://www.ray.io
- Pricing model
- Ray is open source. Anyscale’s hosted offering lists a $100 starting credit, usage-based compute pricing, and contract options.
- Platform
- Python ecosystem, self-managed clusters, cloud infrastructure
- Privacy relevance
- Data handling depends on self-managed infrastructure or the selected hosted provider; evaluate the applicable hosting and privacy terms.
- Strengths
- Distributed-computing focus; open-source project; hosted Anyscale option provides public usage-pricing context.
- Limitations
- It is infrastructure rather than an end-user AI assistant; operating clusters requires significant technical expertise and can incur cloud costs.
- Last reviewed
- 2026-08-27