Overview Leaderboard Methodology
Industry Report

Cloud Database Platforms

Managed database services provided by cloud vendors that offer scalable, fully managed relational and NoSQL databases with integrated backups and monitoring.

Brands tracked: 29
Brands analyzed: 29
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 239
Total responses: 1,190
Top Brand Overall?
Amazon
95/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Google
100

Highest score on the LBA metric in this industry.

Authority Leader?
Amazon
96

Highest score on the Authority metric in this industry.

TOM Leader?
Amazon
100

Highest score on the TOM metric in this industry.

Amazon is the default answer in AI responses for Cloud Database Platforms

When users ask ChatGPT, Claude, or Gemini about Cloud Database Platforms, Amazon is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Google is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 29 Cloud Database Platforms 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
Amazon
amazon.com
 90
96
100
95
2
Google
google.com
 100
54
86
78
3
MongoDB
mongodb.com
 90
68
59
71
4
Microsoft
microsoft.com
 89
47
79
70
5
Supabase
supabase.com
 77
38
40
49
6
Neon
neon.tech
 81
29
30
42
7
Snowflake
snowflake.com
 95
9
46
37
8
CockroachDB
cockroachlabs.com
 82
8
40
32
9
PlanetScale
planetscale.com
 79
16
22
31
10
Oracle
oracle.com
 81
8
16
24
11
Redis
redis.io
 85
9
12
22
12
IBM
ibm.com
 88
9
9
21
13
Couchbase
couchbase.com
 82
8
8
20
14
DataStax
datastax.com
 84
8
8
20
15
DigitalOcean
digitalocean.com
 83
8
8
20
16
ScyllaDB
scylladb.com
 82
8
8
20
17
Heroku
heroku.com
 78
8
8
19
18
SingleStore
singlestore.com
 76
8
8
19
19
TiDB
pingcap.com
 78
8
8
19
20
Aiven
aiven.io
 73
7
7
18
21
Timescale
timescale.com
 76
8
8
18
22
Alibaba Cloud
alibabacloud.com
 69
7
7
17
23
YugabyteDB
yugabyte.com
 70
7
7
17
24
TencentDB
tencent.com
 67
7
7
16
25
Turso
turso.tech
 67
7
7
16
26
Render
render.com
 60
6
6
15
27
Crunchy Bridge
crunchydata.com
 57
6
6
14
28
Memgraph
memgraph.com
 58
6
6
14
29
ElephantSQL
elephantsql.com
 50
5
5
13

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 239 shared Cloud Database 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
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 239 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 →