Thunderdome B2B SaaS AI Visibility Index

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September 2026 snapshot · 72 AI answers Leader emerging

Data Integration & ETL: AI Visibility Ranking

Pipelines for syncing SaaS and database data into warehouses, and reverse ETL. Right now, Fivetran is the brand AI assistants recommend most, with a Visibility Score of 69 and the #1 spot in 44% of answers. Head-to-head: Fivetran vs Airbyte →

These rankings are measured from what the three models know from training, not a live web search. When the models DO search the web, see which sources they cite. Methodology.

Fivetran leads, but Airbyte is close enough to threaten.

Fivetran's 14-point margin over Airbyte looks comfortable until you notice Airbyte appears in 68% of answers and beats Fivetran on ChatGPT. Fivetran's strength is concentrated in Gemini, where it scores 82.5 against Airbyte's 57.9, so any shift in how Gemini weights recommendations could tighten this race fast. Informatica's first-pick rate of 17% is surprisingly high given its overall score of 29.7, suggesting it still commands attention in enterprise-framed questions even as its mention rate trails the top two.

AI-generated analysis of the September 2026 measurements.

# Brand Visibility Score Trend (3 mo) Mention rate Avg. position #1 pick rate Models
1 Fivetran
69
±4.4
Jul 2026: 66.5 · Aug 2026: 66.4 · Sep 2026: 69 flat 79% 2.3 44% ChatGPT #1 Claude #1 Gemini #1
2 Airbyte
55
±4.7
Jul 2026: 53.1 · Aug 2026: 54.7 · Sep 2026: 55.3 flat 68% 2.9 8% ChatGPT #2 Claude #2 Gemini #2
3 dbt
31
±6.5
Jul 2026: 26.4 · Aug 2026: 36.4 · Sep 2026: 30.6 flat 49% 4.7 3% ChatGPT #4 Claude #3 Gemini #4
4 Informatica
30
±5.7
Jul 2026: 29 · Aug 2026: 22.8 · Sep 2026: 29.7 flat 38% 3.1 17% ChatGPT #3 Claude #4 Gemini #3
5 Stitch
17
±5.5
Jul 2026: 19.7 · Aug 2026: 15.4 · Sep 2026: 16.7 flat 24% 3.9 0% ChatGPT #7 Claude #6 Gemini #11
6 Hightouch
14
±2.2
Jul 2026: 13.1 · Aug 2026: 13.2 · Sep 2026: 14.3 flat 19% 3.8 8% ChatGPT #6 Claude #12 Gemini #8
7 Talend
14
±3.9
Jul 2026: 11.9 · Aug 2026: 10.3 · Sep 2026: 13.9 flat 26% 5.7 0% ChatGPT #10 Claude #5 Gemini #15
8 Census
14
±1.9
Jul 2026: 12.6 · Aug 2026: 12.6 · Sep 2026: 13.8 flat 18% 3.4 4% ChatGPT #8 Claude #11 Gemini #10
9 Azure Data Factory
13
±4.2
Jul 2026: 13.2 · Aug 2026: 16.4 · Sep 2026: 13.2 flat 22% 5.1 0% ChatGPT #14 Claude #8 Gemini #6
10 MuleSoft
13
±3.8
Jul 2026: 10.7 · Aug 2026: 9.7 · Sep 2026: 12.5 flat 19% 4.6 3% ChatGPT #13 Claude #7 Gemini #12
11 AWS Glue
13
±3.6
Jul 2026: 16.5 · Aug 2026: 16.4 · Sep 2026: 12.5 flat 24% 5.7 0% ChatGPT #12 Claude #10 Gemini #7
12 Prefect
12
±4.5
Jul 2026: 8.3 · Aug 2026: 11.7 · Sep 2026: 11.9 flat 18% 4.4 3% ChatGPT #9 Claude #9 Gemini #14
13 Meltano
11
±4.1
Jul 2026: 13.3 · Aug 2026: 7.8 · Sep 2026: 10.6 flat 18% 5.2 0% ChatGPT #15 Claude #13 Gemini #5
14 Dagster
9
±4.4
Jul 2026: 13.9 · Aug 2026: 14.3 · Sep 2026: 8.9 flat 14% 4.6 0% ChatGPT #5 Claude #14 Gemini #13
15 Microsoft Fabric
9
±3.9
Jul 2026: 7.8 · Aug 2026: 5 · Sep 2026: 8.8 flat 11% 3.1 1% ChatGPT #11 Claude Gemini #9

The ± under each score is the reliability band: how much the number would move if we re-ran the identical measurement. It is tight because each prompt is sampled multiple times. It is not the same as how much the ranking depends on which prompts we ask — a separate, wider figure shown on hover.

Just below the cutoff: Matillion (8.1), RudderStack (6.7), Microsoft Azure Data Factory (6.4), Snowflake (5.8), IBM DataStage (5.6). 88 brands were scored in this category; the leaderboard shows the top 15.

Visibility Score: position-weighted presence across all measured answers, 0 to 100. A score of 100 means the brand was the first recommendation in every answer. Every point in a trend line is a live monthly measurement; there is no modeled or backfilled history. Full methodology.

Openness 31/100: the share of this category's recommendation weight not held by the leader.

Compare brands in Data Integration & ETL head-to-head →  ·  Explore the prompt tree →

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Do the models agree?

Per-model Visibility Scores for the top 10. A long gray bar means the three assistants disagree about the brand. Hover a row for exact values.

ChatGPT Claude Gemini
0 25 50 75 100 Visibility Score · 0 = never mentioned, 100 = always the first recommendation Fivetran Airbyte dbt Informatica Stitch Hightouch Talend Census Azure Data Factory MuleSoft

Where they land in the answer

When a brand is mentioned, where does it appear? Box shows the middle 50% of positions, the thick line is the median, whiskers are the extremes. Hover a row for the detail.

1 2 3 4 5 6 7 8 9 10 11 12 Position in the answer · 1 = the first product recommended Fivetran Airbyte dbt Informatica Stitch Hightouch Talend Census Azure Data Factory MuleSoft

What each model recommends first

ChatGPT

gpt-5.4

1 Fivetran
68
2 Airbyte
57
3 Informatica
36
4 dbt
24
5 Dagster
20

Claude

claude-sonnet-4-6

1 Fivetran
56
2 Airbyte
51
3 dbt
41
4 Informatica
24
5 Talend
23

Gemini

gemini-3-flash-preview

1 Fivetran
83
2 Airbyte
58
3 Informatica
29
4 dbt
27
5 Meltano
16

The questions we asked

Each model answered every prompt 3 times in September 2026. Prompts are brand-neutral so no vendor gets seeded into the question.

  1. Best overall
    What's the best ETL tool for syncing data into a warehouse? See who wins it →
  2. Use-case fit
    We need to move data from our SaaS apps and Postgres into Snowflake. What should we use? See who wins it →
  3. Top tools in 2026
    What are the top data integration platforms in 2026? See who wins it →
  4. Startup & small team
    Which data pipeline tool is best for a small data team? See who wins it →
  5. Enterprise pick
    Which data integration platform should a large enterprise standardize on, considering security, compliance, and scale? See who wins it →
  6. Feature-led ask
    I want to sync warehouse data back into our CRM and ad tools. What do you recommend? See who wins it →
  7. If you could pick one
    If you could only pick one data integration tool, which one and why? See who wins it →
  8. Budget & alternatives
    What's the best open-source or affordable alternative for data pipelines? See who wins it →