
The AI coding agent for building ambitious software
The AI coding agent for building ambitious software
Datadog records 5,175,760 monthly visits with -4.8% month-over-month growth and Freemium, Free Trial, Paid, Contact for Pricing, Free pricing. RunLLM records 182 monthly visits with -90.6% growth and Free Trial, Contact for Pricing pricing.

The AI SRE that catches production issues before you get paged
| Dimension / Metric | ![]() | |
|---|---|---|
| Official Domain | datadoghq.com | runllm.com |
| Pricing Model | Freemium, Free Trial, Paid, Contact for Pricing, Free | Free Trial, Contact for Pricing |
| Monthly Visits | 5.18M (5,175,760) | 182 (182) |
| MoM Traffic Delta | -263.56K (-4.8%) | -1.76K (-90.6%) |
| Primary Market & Share | 🇺🇸 United States (41.4%) | 🌐 Global (—) |
| Direct Visits / mo | 2.75M | 71 |
| User Rating | 4.7 | 4.4 |
| Supported Platforms | Website | Website |
Unified observability, security and incident response for cloud-scale engineering teams
Agents, cloud integrations and OpenTelemetry collectors feed one platform where metrics, distributed traces, profiles and logs can be pivoted between without context switching.
Bits AI, an agent builder and LLM/AI-agent observability help teams triage alerts, explain anomalies and monitor model latency, token spend and agent traces.
Cloud SIEM, cloud security posture management, vulnerability management, workload protection and code scanning correlate threat signals with the telemetry you already collect.
Real user monitoring, session replay, product analytics, synthetic and mobile testing sit alongside CI visibility, test optimization, feature flags and DORA metrics.

The AI SRE that catches production issues before you get paged
Herald builds a context graph across observability, codebase, CI/CD, docs, and dependencies before alerts fire, so it understands what normal looks like.
No thresholds to tune: Herald builds a custom anomaly detection model for each data stream and surfaces validated issues before customers notice.
The agent evaluates multiple hypotheses at once against the right data sources and delivers root-cause analyses in minutes without runbooks.
100% RCA accuracy on known issues and 70%+ on novel incidents, learning from every investigation so it never repeats a mistake.

The AI coding agent for building ambitious software
The AI coding agent for building ambitious software

Describe your idea and Replit builds a working app in minutes

The coding agent that learns your coding taste
The coding agent that learns your coding taste
GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language

Agent orchestration platform for your whole software development lifecycle
Agent orchestration platform for your whole software development lifecycle

Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI

SpecialistProvides advanced AI-driven threat detection for cloud networks, but focuses purely on security rather than general application performance monitoring.
SpecialistProvides advanced AI-driven threat detection for cloud networks, but focuses purely on security rather than general application performance monitoring.

SpecialistEvaluate, monitor, and govern your AI applications in production
SpecialistEvaluate, monitor, and govern your AI applications in production

SpecialistThe collaboration layer for AI engineering teams
SpecialistThe collaboration layer for AI engineering teams

SpecialistStandardize LLM evaluation, observability, and red teaming across your whole org
SpecialistStandardize LLM evaluation, observability, and red teaming across your whole org
SpecialistAI governance, testing, and observability for regulated enterprises
SpecialistAI governance, testing, and observability for regulated enterprises

SpecialistFocuses on machine learning and LLM model observability, whereas Datadog primarily targets traditional infrastructure and application performance monitoring.
SpecialistFocuses on machine learning and LLM model observability, whereas Datadog primarily targets traditional infrastructure and application performance monitoring.