Portkey vs Ray
On the evidence we track, Portkey leads this comparison with a composite score of 79/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Portkey
LeaderA unified platform combining an AI gateway, observability dashboards, prompt versioning, governance controls, and guardrails. Enables teams to route requests across LLM providers, monitor costs and performance, securely manage API keys, and deploy production-ready prompts with version control.
Ray
Ray is an open-source unified framework for scaling Python and machine learning applications across any infrastructure. It provides distributed compute primitives, specialized AI libraries for data processing, model training, tuning, and serving, with seamless scaling from development environments to large clusters.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Portkey
LeaderFree tier with 10k logs/month. Production at $49/month with usage overages. Enterprise custom pricing for compliance-focused organizations.
- DeveloperFree
- Universal API & Key Management
- Routing, Fallbacks, Load Balancing, Retries
- 3 Prompt Templates with Playground, Versioning, Variables
- Logs, Traces, Feedback, Custom Metadata, Filters
- Simple Caching
- +3 more
- Production$49/month + $9 per 100k request overage
- Universal API, Fallbacks, Load Balancing, Retries
- Unlimited Prompt Templates with Playground, API Deployment, Versioning, Variables
- Logs, Traces, Feedback, Metadata, Filters, Alerts
- LLM & Partner Guardrails
- Role-Based Access Control, Service Account API Keys
- +3 more
- EnterpriseContact sales
- Custom retention periods for logs and metrics
- Advanced Evaluation Templates with custom guardrail hooks
- Role-Based Access Control, SSO (Okta), Granular Budget & Rate Limits
- Private Cloud Deployment, VPC Hosting, Data Export to Data Lakes
- SOC2 Type 2, GDPR, HIPAA compliance certifications
- +3 more
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
Portkey
Leader- OpenAI
- Google Cloud (Vertex AI, Gemini)
- Azure
- AWS
- GCP
- Langgraph
- CrewAI
- Strands Agents
- Google ADK
- Anthropic
- Claude
- Mistral
- MongoDB
- Vertex AI
Ray
- PyTorch
- TensorFlow
- AIBrix
- AReaL
- Cosmos Curate
- Daft
- Data-Juicer
- DeltaCAT
- Modin
- NeMo Curator
- NeMo-RL
- OpenRLHF
- RayDP
- ROLL
- SkyRL
- SLIME
- Syftr
- verl
- vLLM
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.