Datadog LLM vs Langfuse
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.
Langfuse is an open-source LLM observability platform that provides tracing, analytics, prompt management, and evaluation for AI applications. It captures detailed traces of LLM calls, supports custom scoring, and integrates with LangChain, LlamaIndex, Vercel AI SDK, and raw API calls. Langfuse can be self-hosted for data privacy or used as a managed cloud service. Its open-source model and generous free tier make it popular with startups and developers.
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
- Open-source LLM observability
- Detailed trace and span tracking
- Prompt management
- Evaluation scoring
- Self-hosted and cloud options
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
- Fully open-source with MIT license and free for commercial use with no usage limits
- Acquired by ClickHouse in January 2026, providing strong backing and future investment
- Active development with strong community support and comprehensive documentation
- Transparent pricing model based on units rather than complex metric calculations
- Deep integrations with major frameworks like LangChain, OpenAI, and LlamaIndex
Cons
- Recent acquisition by ClickHouse may lead to platform changes and strategic shifts
- Smaller team of 7 employees may impact support capacity
- Enterprise pricing at $3,450-$5,700/month can be expensive for mid-sized teams
Datadog LLM or Langfuse — 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 Langfuse if you wantChoose if you want
- Self-hosted LLM monitoring
- Open-source tracing for AI applications
- Prompt versioning and management
- Cost tracking across providers
- Community-driven observability
Compare Datadog LLM and Langfuse 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.