Datadog LLM vs Helicone
Overview
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.
Helicone is an open-source LLM observability and proxy platform. By adding a single line of code, developers get request logging, cost tracking, caching, rate limiting, and analytics for their LLM applications. Helicone supports all major LLM providers and offers both proxy and async logging modes. Popular with startups for its generous free tier and simple integration.
Key features
Core capabilities each platform advertises.
- LLM monitoring within Datadog platform
- Unified APM + LLM observability
- Automatic instrumentation
- Cost and token tracking
- Integration with existing Datadog dashboards
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Seamless integration with Datadog's full observability suite for unified application monitoring
- Built-in sensitive data scanning and prompt injection detection for enhanced security
- Established enterprise platform with proven reliability and 9,700+ employees globally
- Automatic cost estimation for LLM requests using public pricing models
- Quick setup in seconds using their SDK
Cons
- Premium automatically activated at $120/day when LLM spans detected with no opt-out
- Can be expensive at scale compared to specialized LLM observability tools
- Requires familiarity with Datadog ecosystem for optimal usage
- Per-span pricing model may become costly for high-volume applications
Pros
- Open-source with 5.2K GitHub stars and strong community support
- Minimal latency overhead (under 1ms for self-hosted)
- Flexible deployment options including cloud-hosted, self-hosted, or SDK-only
- Y Combinator-backed with SOC 2 Type II and HIPAA compliance
- No code changes required for AI Gateway features like caching and rate limiting
Cons
- Adds computational cost and one network hop for cloud deployment
- Limited pricing transparency on website
- May require infrastructure expertise for self-hosted setup
Datadog LLM or Helicone — which should you choose?
Choose Datadog LLM if you wantChoose if you want
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
- Compliance and audit logging
- Large-scale production monitoring
Choose Helicone if you wantChoose if you want
Compare Datadog LLM and Helicone on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.