Keywords AI
Arize AI vs Datadog LLM
Compare Arize AI and Datadog LLM side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Freemium | Enterprise |
| Best For | ML teams who need comprehensive observability spanning traditional ML models and LLM applications | Enterprise teams already using Datadog who want to add LLM monitoring |
| Website | arize.com | datadoghq.com |
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When to Choose Arize AI vs Datadog LLM
- Production ML and LLM monitoring
- Embedding quality monitoring
- Model performance tracking
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
About Arize AI
Arize AI provides an ML and LLM observability platform for monitoring model performance in production. For LLM applications, Arize offers trace visualization, prompt analysis, embedding drift detection, and retrieval evaluation. Their open-source Phoenix library provides local tracing and evaluation. Arize helps teams identify quality issues, debug failures, and continuously improve AI system performance.
About Datadog LLM
Datadog's LLM Observability extends its industry-leading APM platform to AI applications. It provides end-to-end tracing from LLM calls to infrastructure metrics, prompt and completion tracking, cost analysis, and quality evaluation—all integrated with Datadog's existing monitoring, logging, and alerting stack. Ideal for enterprises already using Datadog who want unified observability across traditional and AI workloads.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evals tools →