# OpenLIT vs Datadog LLM Observability

> Datadog is a powerful general-purpose observability platform, but LLM monitoring is a paid add-on requiring existing Datadog infrastructure. OpenLIT is purpose-built for AI engineering, open-source, and free to self-host.

- HTML: https://openlit.io/compare/openlit-vs-datadog
- Markdown: https://openlit.io/compare/openlit-vs-datadog.md

Compare OpenLIT and Datadog for LLM observability. OpenLIT is purpose-built, open-source, and free to self-host. Datadog is a general-purpose platform with LLM monitoring as a paid add-on.

## Feature comparison

### Core Architecture

| Feature | OpenLIT | Datadog LLM Observability |
| --- | --- | --- |
| OpenTelemetry-native | Yes | OTel ingestion supported; primary agent is proprietary |
| Open Source | Apache 2.0 | No |
| Self-hostable | Yes | No |
| Purpose-built for LLM / AI engineering | Yes | No |
| Free self-hosted tier | Yes | No |

### LLM Monitoring

| Feature | OpenLIT | Datadog LLM Observability |
| --- | --- | --- |
| Token usage tracking | Yes | Yes |
| Cost per request | Yes | Yes |
| Latency / p95 metrics | Yes | Yes |
| Prompt & response logging | Yes | Yes |
| 60+ integrations (LLMs, frameworks, VectorDBs, GPUs) | Yes | Limited LLM providers supported natively |
| Custom model pricing | Yes | No |

### Infrastructure Monitoring

| Feature | OpenLIT | Datadog LLM Observability |
| --- | --- | --- |
| GPU monitoring (NVIDIA + AMD) | Yes | General GPU metrics only, not LLM-context-aware |
| Vector DB tracing | Yes | No |
| Multi-environment tagging | Yes | Yes |
| Organisation management | Yes | Yes |

### Developer Tools

| Feature | OpenLIT | Datadog LLM Observability |
| --- | --- | --- |
| Prompt Hub (versioning) | Yes | No |
| Evaluations | Yes | Basic (LLM-as-judge) |
| Secrets Vault | Yes | No |
| Fleet Hub (multi-deployment) | Yes | No |
| Out-of-box LLM dashboards | Yes | Requires setup / add-on |
| Unified infra + APM + LLM observability | No | Yes |

### Pricing

| Feature | OpenLIT | Datadog LLM Observability |
| --- | --- | --- |
| Free self-hosted | Yes | No |
| No per-host agent fees | Yes | No |
| No usage-based billing (self-hosted) | Yes | No |
| LLM Observability cost | $0 (self-hosted) | Usage-based paid add-on on top of Datadog subscription |

## When to choose OpenLIT

- You want purpose-built LLM observability without the overhead of a general APM platform
- You need to self-host for data privacy, compliance, or to avoid cloud vendor costs
- You want Prompt Hub, Vault, and Fleet Hub included as part of your AI engineering platform
- You prefer open standards (Apache 2.0, OpenTelemetry) over proprietary agents and lock-in
- You want GPU monitoring that is context-aware of LLM inference, not just system-level GPU metrics

## When to choose Datadog LLM Observability

- You are already invested in Datadog and want a single pane of glass across all infrastructure
- You need enterprise-grade SLAs, SOC 2, HIPAA compliance, and dedicated support contracts
- You want unified alerting across LLM, APM, infrastructure, and logs in one existing platform

## Related

- All comparisons: https://openlit.io/compare.md
- Pricing: https://openlit.io/pricing.md
- Docs: https://docs.openlit.io/latest/openlit/quickstart-ai-observability