DT vs DDOG Stock Comparison: AI Score, Valuation, Performance and Upside
DT and DDOG are the two premier cloud observability platforms, with Datadog leading in breadth (20+ products, broad SMB-to-enterprise market), while Dynatrace focuses on AI-powered causal analysis and deep automation for enterprise environments. Both have strong positions but Datadog has generally demonstrated faster revenue growth and multi-product adoption.
DT vs DDOG is the definitive cloud observability investment comparison, contrasting Dynatrace's AI-causal deep analysis approach against Datadog's broad multi-product platform strategy.
DT and DDOG are closely matched — they split the tracked metrics evenly. DDOG has delivered stronger 1-year price return (+101.77% vs -11.82%), though DT has the better forward P/E setup (19.70x vs 93.19x for DDOG). Analyst consensus implies meaningfully more upside for DT (+6.88%) than for DDOG (+0.74%).
- →Want enterprise observability exposure with particular emphasis on AI-causal root cause analysis
- →See value in Dynatrace's deep code-level automation reducing manual instrumentation work for enterprises
- →Believe European market strength provides geographic diversification versus Datadog's North American concentration
- →Want the broadest cloud observability platform with exceptional multi-product adoption and retention metrics
- →Value Datadog's usage-based pricing and platform expansion strategy across 20+ products
- →Believe Datadog's security platform expansion represents significant incremental revenue opportunity
| Metric | DT | DDOG |
|---|---|---|
| AI score | 32.8 | 53.6 |
| AI rank | #1981 | #294 |
| Latest close | $44.54 | $273.60 |
| 1M return | -0.51% | +5.09% |
| 6M return | +16.93% | +112.01% |
| 1Y return | -11.82% | +101.77% |
How much would $10,000 be worth today if invested at the start of each period, with all dividends reinvested?
| Period | DT | DDOG |
|---|---|---|
| 1Y ago | $8.63K (-13.7%) started 2025-08-04 | $19.67K (+96.7%) started 2025-08-04 |
| 5Y ago | $6.89K (-31.1%) started 2021-08-03 | $23.81K (+138.1%) started 2021-08-04 |
| 10Y ago | $18.68K (+86.8%) started 2019-08-01 | $72.86K (+628.6%) started 2019-09-19 |
Hypothetical — past performance does not guarantee future results.
| Metric | DT | DDOG |
|---|---|---|
| Market cap | $12.98B | $95.39B |
| Trailing P/E | 82.48 | 669.92 |
| Forward P/E | 19.70 | 93.19 |
| Price/Sales | 6.43 | 14.88 |
| EV/Revenue | 5.93 | 25.03 |
| Analyst target | $47.61 | $269.97 |
| Target upside | +6.88% | +0.74% |
| Metric | DT | DDOG |
|---|---|---|
| Revenue growth | 19.40% | 32.20% |
| Earnings growth | -52.60% | 104.00% |
| EPS growth | -52.60% | +104.00% |
| FCF margin | +24.86% | +25.51% |
| Operating margin | N/A | 0.80% |
| Profit margin | 8.06% | 3.69% |
| ROIC proxy | 6.22% | 3.93% |
| Return on equity | 6.22% | 3.93% |
| Dividend yield | 0.00% | N/A |
| Beta | 0.71 | 1.54 |
| Debt/equity | 6.29 | 32.22 |
| Current ratio | 1.35 | 3.40 |
| Quick ratio | 1.22 | 3.29 |
Lower drawdown and smaller single-period drops generally indicate a smoother ride, though they do not guarantee lower future risk.
| Period | Metric | DT | DDOG |
|---|---|---|---|
| 1Y | Growth | -13.70% | +96.65% |
| CAGR | -13.74% | +96.85% | |
| Sharpe ratio | -0.28 | 1.29 | |
| Max drawdown | 37.30% | 48.62% | |
| Max daily drop | 11.43% | 11.28% | |
| Max wkly drop | 15.00% | 18.04% | |
| 5Y | Growth | -31.05% | +138.06% |
| CAGR | -7.17% | +18.95% | |
| Sharpe ratio | -0.09 | 0.51 | |
| Max drawdown | 61.77% | 68.11% | |
| Max daily drop | 17.98% | 17.18% | |
| Max wkly drop | 27.11% | 23.41% | |
| 10Y | Growth | +86.75% | +628.63% |
| CAGR | +9.32% | +33.49% | |
| Sharpe ratio | 0.33 | 0.70 | |
| Max drawdown | 61.77% | 68.11% | |
| Max daily drop | 17.98% | 17.87% | |
| Max wkly drop | 33.58% | 30.02% |
| Category | DT | DDOG |
|---|---|---|
| Company | Dynatrace, Inc. | Datadog, Inc. |
| Sector | Information Technology - Cloud Observability | Technology |
| Industry | N/A | Software - Application |
| Core business | Dynatrace provides an AI-powered observability and security platform called the Dynatrace Platform, using automation and its proprietary Davis AI to provide causal analysis of IT environment problems across applications, infrastructure, and security. | Datadog provides a cloud monitoring and observability platform combining infrastructure monitoring, APM, log management, security, and dozens of other products into a single, cloud-native platform with usage-based pricing. |
| Investor focus | Investors track Dynatrace's annual recurring revenue (ARR) growth, platform product consolidation revenue, and competitive win rates against Datadog in enterprise accounts requiring AI-powered causal analysis. | Investors track Datadog's revenue growth, multi-product adoption depth (customers using 8+ products), net dollar retention, and its security platform growth as a high-margin expansion vector. |
- →Proprietary Davis AI provides causal root cause analysis — finding why a problem occurred, not just detecting it
- →Full-stack observability with deep code-level analysis from automated instrumentation
- →Strong European enterprise customer base complements Datadog's stronger North American presence
- →Broadest product portfolio in cloud observability with 20+ integrated products addressable within a single platform
- →Exceptional multi-product adoption driving highly durable net dollar retention above 120%+
- →Usage-based pricing model aligns with cloud-native workload patterns and simplifies expansion
- →Annual recurring revenue growth has been somewhat slower than Datadog's platform expansion, raising competitive positioning concerns
- →Must articulate distinct value versus Datadog's increasingly AI-enhanced platform
- →More complex enterprise sales cycles due to sophisticated automation and AI capability messaging
- →Premium valuation multiples require continued strong growth and product expansion execution
- →Increasing AI spending may temporarily redirect customer budgets away from traditional monitoring optimization
- →Competition from Dynatrace, Elastic, and emerging AI-native monitoring tools
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