Overview Leaderboard Methodology
Industry Report

Data Integration Platforms

Enterprise-grade solutions that connect, orchestrate, and consolidate data across on-premises and cloud systems for unified access.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,469
Top Brand Overall?
Informatica
80/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
100

Highest score on the LBA metric.

Authority Leader?
Informatica
63

Highest score on the Authority metric.

TOM Leader?
Informatica
100

Highest score on the TOM metric.

Informatica leads the Data Integration Platforms category in AI responses

Informatica is the most consistently-surfaced brand when users ask AI assistants about Data Integration Platforms, but not to the point of monopolising the conversation. Fivetran and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 37 Data Integration Platforms brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Informatica
informatica.com
 81
63
100
80
2
Fivetran
fivetran.com
 81
52
75
68
3
Boomi
boomi.com
 77
24
65
49
4
Talend
talend.com
 76
17
77
46
5
MuleSoft
mulesoft.com
 85
21
50
45
6
Microsoft
microsoft.com
 100
9
77
41
7
Apache
apache.org
 79
31
18
35
8
Airbyte
airbyte.com
 71
31
18
34
9
IBM
ibm.com
 87
8
58
34
10
Matillion
matillion.com
 73
10
37
30
11
Google
google.com
 78
19
17
29
12
dbt
dbt.com
 89
2
26
16
13
Workato
workato.com
 79
5
1
8
14
SnapLogic
snaplogic.com
 77
0
47
3
15
Meltano
meltano.com
 59
0
1
2
16
Denodo
denodo.com
 70
0
1
1
17
Pentaho
pentaho.com
 73
0
1
1
18
Stitch
stitchdata.com
 65
0
1
1
19
Adeptia
adeptia.com
 49
0
0
0
20
Adverity
adverity.com
 65
0
0
0
21
Amazon
amazon.com
 77
0
0
0
22
Astera
astera.com
 67
0
0
0
23
BryteFlow
bryteflow.com
 36
0
0
0
24
CData
cdata.com
 72
0
0
0
25
Celigo
celigo.com
 66
0
0
0
26
CloverDX
cloverdx.com
 65
0
0
0
27
Data Virtuality
datavirtuality.com
 55
0
0
0
28
Etleap
etleap.com
 45
0
0
0
29
Hevo Data
hevodata.com
 64
0
0
0
30
Integrate.io
integrate.io
 59
0
0
0
31
Jitterbit
jitterbit.com
 73
0
0
0
32
Keboola
keboola.com
 61
0
0
0
33
Portable
portable.io
 37
0
0
0
34
Precisely
precisely.com
 75
0
0
0
35
Rivery
rivery.io
 58
0
0
0
36
Skyvia
skyvia.com
 60
0
0
0
37
StreamSets
streamsets.com
 70
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Data Integration Platforms 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 287 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 →