Every category where a model named Matillion 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
ETL and ELT	Data platform	0%	12 of 66	12%	26	accepted challenger

Movement

This is the first edition on this tier, so no move can be computed for Matillion 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 Matillion across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	1	0	0	1
GPT-5.4 mini	1	0	1	2
Gemini 3.5 Flash	0	1	0	1
Perplexity Sonar	2	0	0	2
Grok 4.1 Fast	0	2	1	3
Mistral Small	0	2	0	2
DeepSeek V4 Flash	1	1	1	3
Llama 4 Maverick	0	1	0	1
Qwen 3.7 Flash	1	0	0	1
Kimi K2	2	2	0	4
GLM 4.7 FlashX	3	0	0	3
MiniMax M2.5	1	2	0	3

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

Direct13 labels2

Paraphrase11 labelsNone

Comparative26 labelsNone

Budget-constrained4 labelsNone

Scale-constrained14 labelsNone

Negative9 labelsNone

First choiceAlternativeMentionNegative77 labels in all, every segment counted; 2 of the 2 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.

“Matillion | Teams committed to specific cloud warehouses (Snowflake/BigQuery/Redshift)” Kimi K2 · ETL · scale prompt · alternative

“If you are fully on Snowflake/BigQuery, Matillion is often the most performant.” Qwen 3.7 Flash · ETL · comparative prompt · alternative

“Choose Matillion if your team prefers a visual, warehouse-centric ETL tool.” Perplexity Sonar · ETL · comparative prompt · alternative

“Choose Matillion if your team wants more visual, transformation-heavy ETL” Perplexity Sonar · ETL · direct prompt · alternative

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.

“Matillion’s docs note limitations such as FTPS not being supported in a component ... security docs also warn about public exposure” GPT-5.4 mini · ETL · negative prompt · soft negative

“No-Code/Low-Code Tools (general category, e.g., some Matillion or drag-and-drop platforms)... Hidden costs at scale” Grok 4.1 Fast · ETL · negative prompt · soft negative

“Pricing is a common pain point: ... charged based on VM uptime” DeepSeek V4 Flash · ETL · negative prompt · soft negative

Named alongside

The products named in the same answers as Matillion, over the 77 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Matillion was named but was not.

ProductSame answerTook the first choice insteadHead to head

Fivetran71 of 7728Not in the top three

Airbyte65 of 779Not in the top three

Talend43 of 770Not in the top three

dbt36 of 770Not in the top three

Stitch35 of 775Not in the top three

Hevo Data30 of 771Not in the top three

Integrate.io29 of 778Not in the top three

Informatica27 of 772Not in the top three

AWS Glue25 of 770Not in the top three

Apache Airflow21 of 770Not 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 Matillion. 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 63 of the 77 answers that named Matillion and are not a share of its labels.

Domains cited

integrate.io50

hevodata.com42

sqream.com28

fivetran.com27

estuary.dev22

airbyte.com20

datacamp.com20

skyvia.com20

stacksync.com20

weld.app19

268 of the 268 domain citations in answers naming Matillion came from somebody else's page.

Pages cited

integrate.io/blog/top-7-etl-tools38

sqream.com/blog/best-etl-tools28

datacamp.com/blog/a-list-of-the-16-best-etl-tools-and-why-to-choose-them20

stacksync.com/blog/26-best-etl-tools-2025-curated-list19

estuary.dev/blog/etl-tools-list17

fivetran.com/learn/etl-tools17

dataquest.io/blog/etl-tools-practical-guide-with-examples15

weld.app/blog/etl-tools-compared14

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 Matillion'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 Matillion, 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 matillion.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.