AIOps platforms · October 2026 Edition
Datadog vs PagerDuty AIOps
Five of fourteen models named Datadog first on the direct prompt; zero named PagerDuty AIOps. Datadog was named by thirteen of the fourteen models and PagerDuty AIOps by seven and Datadog carries 40 labels and PagerDuty AIOps 10, so the shares are not directly comparable.
Named in eight categories this edition.
Named in one category this edition.
First-choice share15%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate15%30%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#5A position in a field of 10; printed, not drawn.
Labels4010A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Datadog reading right to left. Rank and label count are printed, not drawn.New Relic was named alongside these two in twelve of the fourteen direct answers. New Relic vs Datadog · New Relic vs PagerDuty AIOps · Datadog vs Dynatrace
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the aiops platforms page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DatadogFirst choices, of fourteen modelsPagerDuty AIOps
Direct501 against Datadog
Paraphrase33
Comparative20
Budget-constrained002 against Datadog · 1 against PagerDuty AIOps
Scale-constrained00
Negative003 against Datadog · 2 against PagerDuty AIOps
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Datadog and PagerDuty AIOps stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | ||||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | ||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | | | | | ||
| Mistral Small | | |||||
| DeepSeek V4 Flash | | | ||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | | | ||||
| Kimi K2 | | | | |||
| GLM 4.7 FlashX | | | | | | |
| MiniMax M2.5 | | | ||||
| GPT-6 Luna | | | | | ||
| Muse Glimmer 30B | | | | |
Datadog PagerDuty AIOps first choice named as an alternative argued againstblank: not namedEach cell is one answer, Datadog on the left and PagerDuty AIOps on the right.The direct prompt
The plain question, one answer per model, grouped by where Datadog and PagerDuty AIOps stood in it.
Datadog first, PagerDuty AIOps not the choice
5 of 14 modelsPagerDuty AIOps was named in the answer but not as the choice, or not at all.Gemini 3.5 FlashDatadog, LogicMonitor alternatives: New Relic, PagerDuty
Grok 4.1 FastDatadog alternatives: New Relic
MiniMax M2.5Datadog, New Relic alternatives: Dynatrace
GPT-6 LunaDatadog alternatives: Dynatrace, New Relic
Muse Glimmer 30BDatadog, Dynatrace, New Relic alternatives: Freshservice
Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniDynatrace alternatives: Datadog, New Relic, Splunk
Qwen 3.7 FlashDynatrace alternatives: BigPanda, Datadog, Elastic Observability, Grafana Cloud, OpenTelemetry
Kimi K2New Relic alternatives: Datadog, LogicMonitor
GLM 4.7 FlashXDynatrace alternatives: Datadog, Freshservice, ManageEngine OpManager Nexus, New Relic
Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5PagerDuty alternatives: BigPanda, LogicMonitor, New Relic
Perplexity SonarNew Relic alternatives: Coralogix
Mistral SmallDynatrace alternatives: BigPanda, LogicMonitor, New Relic
DeepSeek V4 FlashLogicMonitor, New Relic alternatives: BigPanda, Freshservice, PagerDuty
Llama 4 MaverickDynatrace
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Datadog leads by three points.
Datadog10%#3 of 16PagerDuty AIOps7%#6 of 16Mid-marketThe figures above
Datadog leads by nine points.
Datadog15%#2 of 10PagerDuty AIOps6%#5 of 10Enterprise
Datadog leads by four points.
Datadog4%#4 of 11PagerDuty AIOps0%#– of 11What the models said about Datadog
No label in this category carried a quote.
What the models said about PagerDuty AIOps
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“It charges by accepted events, so model your real event stream—including spikes and maintenance windows—before signing.” GPT-6 Luna · negative prompt · soft negative
“though some users find per-user costs steep, so it's best to evaluate their pricing carefully” Mistral Small · budget prompt · soft negative
“Users report steep pricing and a "really struggling in the current market" vibe” GLM 4.7 FlashX · negative prompt · soft negative
“For a typical mid-sized B2B company, PagerDuty AIOps offers the best balance of capability, cost transparency, and ease of deployment.” DeepSeek V4 Flash · paraphrase prompt · first choice
“I'd generally recommend PagerDuty AIOps / Signal Intelligence as the best starting point” GPT-5.4 mini · paraphrase prompt · first choice
“My default recommendation: PagerDuty AIOps” GPT-6 Luna · paraphrase prompt · first choice
Also compared
New Relic vs DatadogNew Relic vs PagerDuty AIOpsDatadog vs DynatraceDatadog vs BigPandaDatadog vs LogicMonitorDatadog vs PagerDutyDynatrace vs PagerDuty AIOpsBigPanda vs PagerDuty AIOpsPagerDuty AIOps vs LogicMonitorPagerDuty AIOps vs PagerDutyAll twenty-one head-to-head pages and the full aiops standing
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.