FullStory vs Datadog
Side-by-side comparison to help you choose the best tool.
FullStory
freemiumFullStory is a digital experience intelligence platform that captures every user interaction and uses AI to surface friction, drop-off points, and bugs across web and mobile. Its AI features include auto-generated session data, frustration signal detection, and DX Data - a structured dataset derived from behavioural signals. FullStory bridges the gap between quantitative analytics and qualitative session replay.
Datadog
paidDatadog is a cloud-scale observability and security platform that monitors infrastructure, applications, and logs in real time. Its AI features include Watchdog - an autonomous anomaly detection engine - plus Bits AI, a natural language assistant that helps engineers investigate incidents, query logs, and understand distributed traces without digging through dashboards manually.
| Feature | FullStory | Datadog |
|---|---|---|
| Pricing | freemium | paid |
| Category | Data & Analytics | Data & Analytics |
| Rating | 4.5 | 4.6 |
| Best For | Product and engineering teams wanting complete session capture with AI insight generation to identify and fix UX friction | DevOps and SRE teams monitoring cloud infrastructure and applications at scale |
| Views | 5 | 6 |
Pros
- Captures every interaction without sampling
- AI frustration detection identifies UX problems automatically
- DX Data enables analytics on behavioural signals
Cons
- Can be expensive at enterprise scale
- Full capture creates large data volumes to manage
Pros
- Comprehensive full-stack observability
- Powerful AI anomaly detection
- Extensive integrations (600+)
Cons
- Costs escalate quickly at scale
- Can be complex to configure for beginners
- Full session capture & replay
- AI frustration signal detection
- DX Data structured behavioural dataset
- Funnel & conversion analysis
- Error tracking integration
- AI anomaly detection (Watchdog)
- Bits AI natural language queries
- APM & distributed tracing
- Log management
- Infrastructure monitoring