Small business▼−6Since September 2026: 12% → 6%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
6%from 12% in September 2026
Inside the floor by 5 pointsRank 3 → 4 of 92
Fivetran · 5 categories · RankedCensus
262Judge labels
35First choices
43Negative labels
14 / 14Models named it
5Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Best standing
13% in Warehouse & ETL for enterprise buyers
Rank 4 of 83 in the mid-market standingaccepted challenger
2 of 14 models made it the first choice on the direct prompt; 12% of its 80 labels there were negative.
What the models named instead of Census →By buyer segmentRead the same way at every buyer size.
Small business3 of 99
7%61 labels
criticized challenger
Mid-market4 of 83
11%80 labels
accepted challenger
Enterprise3 of 82
13%70 labels
accepted challenger
In warehouse & etl · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Census for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data warehouse and reverse ETL for marketing | GTM data and infrastructure | 11% | 4 of 83 | 12% | 80 | accepted challenger | ▲+6Since September 2026: 5% → 12%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Customer data platforms | GTM data and infrastructure | 2% | 6 of 61 | 0% | 11 | accepted challenger | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data management platforms | GTM data and infrastructure | 0% | 28 of 159 | 0% | 6 | under 10 labels · led by Segment at 37% | ▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Identity resolution | GTM data and infrastructure | 0% | 35 of 140 | 0% | 4 | under 10 labels · led by Hightouch Adaptive Identity Resolution at 12% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Customer intelligence and data science | GTM data and infrastructure | 0% | 86 of 142 | 0% | 1 | under 10 labels · led by Amplitude at 18% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Census held within the floor in all five categories: no change cleared 11 points.
Best category · Warehouse & ETL · by segment
Mid-market▲+6Since September 2026: 5% → 12%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
12%from 5% in September 2026
Inside the floor by 5 pointsRank 4 of 81, unchanged
Enterprise=heldSince September 2026: 10% → 10%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
10%from 10% in September 2026
Inside the floor by 11 pointsRank 4 → 3 of 79
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Warehouse & ETL | 5% | 12% | ▲+6Since September 2026: 5% → 12%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 4 of 83, unchanged |
| CDP | 0% | 2% | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 14 → 6 of 61 |
| DMP | 2% | 0% | ▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 13 → 28 of 159 |
| Identity | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 33 → 35 of 140 |
| Customer intel | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 43 → 86 of 142 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated Census across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Census across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 2 | 1 | 1 | 5 |
| GPT-5.4 mini | 1 | 2 | 1 | 0 | 4 |
| Gemini 3.5 Flash | 4 | 8 | 6 | 0 | 18 |
| Perplexity Sonar | 1 | 1 | 1 | 0 | 3 |
| Grok 4.1 Fast | 2 | 5 | 0 | 1 | 8 |
| Mistral Small | 3 | 0 | 1 | 2 | 6 |
| DeepSeek V4 Flash | 2 | 4 | 0 | 1 | 7 |
| Llama 4 Maverick | 0 | 1 | 5 | 0 | 6 |
| Qwen 3.7 Flash | 0 | 7 | 1 | 0 | 8 |
| Kimi K2 | 0 | 6 | 2 | 1 | 9 |
| GLM 4.7 FlashX | 0 | 6 | 0 | 1 | 7 |
| MiniMax M2.5 | 2 | 2 | 1 | 1 | 6 |
| GPT-6 Luna | 1 | 2 | 4 | 1 | 8 |
| Muse Glimmer 30B | 0 | 4 | 2 | 1 | 7 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct41 labels6
Paraphrase41 labels6
Comparative42 labels7not counted in share
Budget-constrained37 labels4
Scale-constrained54 labels19
Negative47 labels3not counted in share
First choiceAlternativeMentionNegative262 labels in all, every segment counted; 35 of the 45 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
“compare Hightouch with Fivetran Activations (the current Fivetran product incorporating Census reverse-ETL capabilities)” GPT-6 Luna · Warehouse & ETL · scale prompt · first choice
“Both industry-leading Reverse ETL platforms offer a permanent free tier of 1 active destination with unlimited syncs/runs.” Gemini 3.5 Flash · Warehouse & ETL · budget prompt · first choice
“BigQuery + Fivetran + dbt + Census + Looker Studio is the strongest, most cost-effective combination” DeepSeek V4 Flash · Warehouse & ETL · direct prompt · first choice
“Similar to Hightouch, focused on activating warehouse data across downstream business apps” Perplexity Sonar · Warehouse & ETL · comparative prompt · first choice
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Don't rush into dedicated reverse ETL tools (especially Census post-acquisition)... this is the one I'd flag most strongly as "be cautious."” DeepSeek V4 Flash · Warehouse & ETL · negative prompt · hard negative
“Census assumes your data is already clean and modeled... You need a data engineering team or analytics engineer managing warehouse hygiene before Census delivers value.” Claude Haiku 4.5 · Warehouse & ETL · negative prompt · soft negative
“Pricing model shift: Moved from flat-fee to consumption-based Monthly Active Rows (MAR), making costs harder to predict” MiniMax M2.5 · Warehouse & ETL · negative prompt · soft negative
“"Users find Fivetran's pricing to be quite expensive, which limits accessibility and flexibility for wider usage."” Muse Glimmer 30B · Warehouse & ETL · negative prompt · soft negative
Named alongside
The products named in the same answers as Census, over the 250 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Census was named but was not.ShowHide
Named alongside
The products named in the same answers as Census, over the 250 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Census was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named Census. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 224 of the 250 answers that named Census and are not a share of its labels.
Domains cited
improvado.io148
hightouch.com97
guideflow.com95
cdp.com77
aboutmartech.com61
leadjourney.io61
airbyte.com55
integrate.io54
skyvia.com51
portermetrics.com50
749 of the 749 domain citations in answers naming Census came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
fivetran.com is not in Google's top ten for any of the category's searches. In the answers, Census takes 11% of first choices and Hightouch takes 40%.ShowHide
Search and answers
fivetran.com is not in Google's top ten for any of the category's searches. In the answers, Census takes 11% of first choices and Hightouch takes 40%.
ShowHideIn search
Google, US estimatesPosition for “marketing data warehouse and reverse etl stack”
–
not in the top ten
Position for “best marketing data warehouse and reverse etl stack”
–
not in the top ten
- Searches for its name, Google
- 60,500 a month (“census”)
- AI search demand for its name, est.
- 14,424 a month
- Its company's site
- fivetran.com shared with Fivetran's other products; the figures are the site's
- Organic visits to its site
- about 41,501 a month
- Searches its site ranks for
- 9,221 · 496 in the top three
- Sites linking to it
- 7,595
- Paid Google search
- 3 searches its ads show for, about 6 clicks and $126 a month (estimate)
In answers
This editionShare of first choices
11%
rank 4 of 83 in Warehouse & ETL
Segment leader
40%
Hightouch
- First choices
- 35 across its categories
- Named in
- 250 answers
- Its own site cited
- in 224 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
Names read as Census
What the judge wrote, as written, with how often. The vendor table decides that these count as Census; a claim can dispute any of them.
Fivetran Activations 7Census / Fivetran Activations 4Census (now Fivetran Activations) 2Census (Fivetran Activations) 1Census (Fivetran) 1Census (now "Fivetran Activations") 1Fivetran / Fivetran Census 1Fivetran Census (formerly Census) 1
Follow Census
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
Fivetran is the company behind Census.ShowHide
The company
Fivetran is the company behind Census.
ShowHideOn record
Wikidata- Website
- fivetran.com
- Headquarters
- United States
- Also from Fivetran
- Fivetran Reverse ETL
Fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata · LinkedIn · Crunchbase
Is this your product?
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Census's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Census, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Census by email, built from the raw record of the edition. It shows:
- where Census is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Census, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.