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

AI Observability

LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.

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Starting Price

Free

Feature Comparison

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FeatureDatadog LLM ObservabilityLangSmith
CategoryData AnalysisAI Observability
Pricing Plans40 tiers59 tiers
Starting PriceContact for pricingFree
Key Features
  • End-to-end LLM tracing
  • Infrastructure correlation
  • Cost tracking
  • Tracing for any LLM stack via Python/TypeScript SDKs or OpenTelemetry
  • LLM-as-judge, code-based and pairwise evaluations
  • Versioned prompts with production A/B traffic splits

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

  • Best-in-class integration if you already use LangChain or LangGraph.
  • Eval suites are practical enough to actually gate releases on, not just dashboards.
  • Self-hosted Enterprise tier covers SOC 2 and regulated environments.

Cons

  • Per-trace pricing on Plus surprises teams that scale production traffic quickly.
  • Non-LangChain stacks work but trade ergonomic polish for SDK overhead.
  • Some eval features require additional LLM spend on top of the platform fee.

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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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