Datadog LLM Observability vs LangSmith

Detailed side-by-side comparison to help you choose the right tool

Datadog LLM Observability

Data Analysis

Enterprise-grade monitoring for AI agents and LLM applications built on Datadog's infrastructure platform. Tracks prompts, responses, costs, and performance across multi-agent workflows. Pricing scales with LLM span volume.

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Starting Price

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LangSmith

🔴Developer

Business Analytics

LangSmith lets you trace, analyze, and evaluate LLM applications and agents with deep observability into every model call, chain step, and tool invocation.

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Starting Price

Free

Feature Comparison

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FeatureDatadog LLM ObservabilityLangSmith
CategoryData AnalysisBusiness Analytics
Pricing Plans40 tiers8 tiers
Starting PriceContact for pricingFree
Key Features
  • End-to-end LLM tracing
  • Infrastructure correlation
  • Cost tracking
  • Workflow Runtime
  • Tool and API Connectivity
  • State and Context Handling

Datadog LLM Observability - Pros & Cons

Pros

  • Seamless integration with existing Datadog infrastructure and APM monitoring creates unified observability
  • Automatic LLM span detection and instrumentation requires minimal setup for popular frameworks
  • Production-based experiment generation uses real data for more accurate A/B testing results
  • Enterprise-grade security, compliance, and governance features meet strict organizational requirements
  • Correlation between LLM performance and infrastructure metrics helps identify root causes quickly

Cons

  • Span-based billing can result in unexpectedly high costs for high-volume LLM applications
  • Requires Datadog platform knowledge and often additional Datadog products for full value
  • More expensive than specialized AI monitoring tools for teams only tracking LLM applications
  • No transparent pricing makes cost planning difficult for budget-conscious teams

LangSmith - Pros & Cons

Pros

  • Comprehensive observability with detailed trace visualization
  • Native MCP support for universal agent tool deployment
  • Generous free tier for individual developers and small projects
  • No-code Agent Builder reduces technical barriers
  • Managed deployment infrastructure with production-ready scaling
  • Strong integration with entire LangChain ecosystem

Cons

  • Primarily designed for LangChain applications (limited framework support)
  • Steep pricing jump from Plus to Enterprise tier
  • Pay-as-you-go model can become expensive for high-volume applications
  • Enterprise features require annual contracts
  • 14-day retention on base traces may be insufficient for some use cases

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🔒 Security & Compliance Comparison

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Security FeatureDatadog LLM ObservabilityLangSmith
SOC2✅ Yes✅ Yes
GDPR✅ Yes✅ Yes
HIPAA✅ Yes
SSO✅ Yes✅ Yes
Self-Hosted❌ No🔀 Hybrid
On-Prem❌ No✅ Yes
RBAC✅ Yes✅ Yes
Audit Log✅ Yes✅ Yes
Open Source❌ No❌ No
API Key Auth✅ Yes✅ Yes
Encryption at Rest✅ Yes✅ Yes
Encryption in Transit✅ Yes✅ Yes
Data ResidencyMultiple regions availableUS, EU
Data RetentionConfigurableconfigurable
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