Overview Leaderboard Methodology
Industry Report

Log Management Services

Cloud and on-premise services that ingest, index, and query application and infrastructure logs for search, alerting, and forensic analysis.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Datadog
94/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Elastic
90

Highest score on the LBA metric in this industry.

Authority Leader?
Datadog
98

Highest score on the Authority metric in this industry.

TOM Leader?
Datadog
100

Highest score on the TOM metric in this industry.

Datadog is the default answer in AI responses for Log Management Services

Datadog and Splunk together dominate AI responses for Log Management Services. 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 34 Log Management Services 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
 84
98
100
94
2
Splunk
splunk.com
 82
96
97
92
3
Elastic
elastic.co
 90
65
81
78
4
Grafana
grafana.com
 82
43
50
56
5
Sumo Logic
sumologic.com
 74
35
67
56
6
New Relic
newrelic.com
 86
11
47
38
7
Microsoft
microsoft.com
 85
16
34
37
8
Amazon Web Services
aws.amazon.com
 86
9
16
25
9
Graylog
graylog.org
 70
7
24
25
10
Papertrail
papertrail.com
 69
7
27
25
11
IBM
ibm.com
 78
8
15
23
12
Google Cloud
cloud.google.com
 87
9
9
21
13
Loggly
loggly.com
 67
7
13
20
14
Logz.io
logz.io
 72
7
10
19
15
Better Stack
betterstack.com
 73
7
7
18
16
Coralogix
coralogix.com
 73
7
7
18
17
Devo
devo.com
 73
7
7
18
18
LogRhythm
logrhythm.com
 70
7
7
17
19
Edge Delta
edgedelta.com
 63
6
6
16
20
Humio
humio.com
 67
7
7
16
21
ManageEngine ServiceDesk Plus
manageengine.com
 67
7
7
16
22
Mezmo
mezmo.com
 64
6
6
16
23
Nagios
nagios.com
 65
6
6
16
24
Scalyr
scalyr.com
 60
6
6
15
25
Sematext
sematext.com
 62
6
6
15
26
LogPoint
logpoint.com
 57
6
6
14
27
Logit.io
logit.io
 52
5
5
13
28
Axiom
axiom.co
 46
5
5
12
29
OpenObserve
openobserve.ai
 47
5
5
12
30
S
Sawmill
sawmill.net
 41
4
4
11
31
observIQ
observiq.com
 39
4
4
10
32
DNIF
dnif.it
 33
3
3
9
33
Last9
last9.io
 35
3
3
9
34
Motadata ServiceOps
motadata.com
 33
3
3
9

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Log Management Services 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 269 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 →