Finance AI Index
Index Vendors › Fivetran · September 2026 Edition
2 categories · Named, not ranked

Fivetran

9Judge labels
0First choices
2Negative labels
7 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.
Standing
4 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Fivetran was named 4 times in Financial consolidation and 1 other category, where Prophix led with 19%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In financial consolidation · 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 Fivetran 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.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Financial consolidationAccounting and close0%25 of 960%3under 10 labels · led by Prophix at 19%
Financial reporting and dashboardsPlanning and analysis0%107 of 133100%1under 10 labels · led by Sage Intacct at 27%

Movement

This is the first edition on this tier, so no move can be computed for Fivetran yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Fivetran across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini10001
Gemini 3.5 Flash00101
Perplexity Sonar00000
Grok 4.1 Fast00011
Mistral Small00000
DeepSeek V4 Flash00101
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500000

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
Direct1 labelNone
Paraphrase0 labelsNone
Comparative6 labels3not counted in share
Budget-constrained0 labelsNone
Scale-constrained0 labelsNone
Negative2 labelsNone
First choiceAlternativeMentionNegative9 labels in all, every segment counted; 0 of the 3 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.

“Choose Fivetran or Matillion if you want mostly automated cloud data consolidation into a warehouse.” GPT-5.4 mini · Financial consolidation · 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.

“Frequent sync failures, slow support response times, high costs due to Monthly Active Rows (MAR) pricing that scales unpredictably” Grok 4.1 Fast · Financial reporting · negative prompt · soft negative

Named alongside

The products named in the same answers as Fivetran, over the 9 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Fivetran was named but was not.
ProductSame answerTook the first choice insteadHead to head
Airbyte5 of 90Not in the top three
Hevo Data4 of 90Not in the top three
OneStream3 of 93Not in the top three
Oracle Fusion Cloud EPM3 of 90Not in the top three
Qlik Talend3 of 90Not in the top three
CCH Tagetik2 of 91Not in the top three
BlackLine2 of 90Not in the top three
Domo2 of 90Not in the top three
Informatica2 of 90Not in the top three
Matillion2 of 90Not in the top three
A head-to-head page exists where both products are in a category's top three. 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 Fivetran. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 7 of the 9 answers that named Fivetran and are not a share of its labels.

Domains cited

gartner.com3
hevodata.com3
worldmetrics.org3
airbyte.com2
cfoshortlist.com2
fivetran.comYour site2
linkedin.com2
onestream.com2
peliqan.io2
zipdo.co2

Twenty-one of the twenty-three domain citations in answers naming Fivetran came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

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 Fivetran'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 Fivetran, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at fivetran.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

Subscribe to the pack