Overview Leaderboard Methodology
Industry Report

Distributed Tracing Solutions

Tools that instrument and correlate requests across microservices to visualize request flows, latency hotspots, and service dependencies.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
Datadog
89/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Datadog APM
90

Highest score on the LBA metric in this industry.

Authority Leader?
Datadog
89

Highest score on the Authority metric in this industry.

TOM Leader?
Datadog
98

Highest score on the TOM metric in this industry.

Datadog is the default answer in AI responses for Distributed Tracing Solutions

Datadog and Grafana together dominate AI responses for Distributed Tracing Solutions. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 33 Distributed Tracing Solutions brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Datadog
datadoghq.com
 81
89
98
89
2
Grafana
grafana.com
 83
75
87
82
3
Honeycomb
honeycomb.io
 87
64
74
74
4
New Relic
newrelic.com
 83
57
67
68
5
Jaeger
jaegertracing.io
 85
50
69
66
6
Datadog APM
datadog.com
 90
49
63
65
7
OpenTelemetry
opentelemetry.io
 79
53
63
64
8
Dynatrace
dynatrace.com
 87
35
60
57
9
Elastic
elastic.co
 84
9
29
30
10
Amazon
amazon.com
 79
12
18
27
11
Splunk
splunk.com
 86
9
21
27
12
Zipkin
zipkin.io
 77
8
24
26
13
Google
google.com
 89
9
12
23
14
Apache
apache.org
 68
7
13
20
15
Sentry
sentry.io
 85
8
8
20
16
Lightstep
lightstep.com
 77
8
8
19
17
AppDynamics
appdynamics.com
 73
7
7
18
18
Instana
instana.com
 75
7
7
18
19
Lumigo
lumigo.io
 70
7
7
17
20
Scout APM
scoutapm.com
 69
7
7
17
21
SigNoz
signoz.io
 67
7
7
17
22
Logz.io
logz.io
 59
6
6
15
23
Tracetest
tracetest.io
 63
6
6
15
24
Glowroot
glowroot.org
 56
6
6
14
25
groundcover
groundcover.com
 56
6
6
14
26
Middleware
middleware.io
 52
5
5
13
27
Uptrace
uptrace.dev
 51
5
5
13
28
Atatus
atatus.com
 48
5
5
12
29
Coroot
coroot.com
 48
5
5
12
30
HyperDX
hyperdx.io
 49
5
5
12
31
A
Aspecto
aspecto.io
 33
3
3
9
32
Pinpoint
pinpointhq.com
 35
3
3
9
33
Dash0
dash0.com
 30
3
3
8

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Distributed Tracing Solutions prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 263 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →