Index › Products › dbt tests · October 2026 Edition

1 category · Named, not ranked

dbt tests

15Judge labels

0First choices

1Negative labels

11 / 14Models named it

1Category

October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.

Standing

7 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. dbt tests was named 7 times in Data observability, where Metaplane led with 31%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business28 of 101

under the label threshold

Mid-market26 of 110

under the label threshold

Enterprisenot named

No model named it for this buyer.

In data observability · 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 dbt tests 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 quality and observability	Data platform	0%	26 of 110	0%	7	under 10 labels · led by Metaplane at 31%

Movement

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

By model

How each model treated dbt tests across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	Alternative	Mention	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	0	0
Gemini 3.5 Flash	0	0	0
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	0	0
Mistral Small	0	0	0
DeepSeek V4 Flash	0	0	0
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	1	1	2
Kimi K2	2	0	2
GLM 4.7 FlashX	1	0	1
MiniMax M2.5	0	0	0
GPT-6 Luna	0	1	1
Muse Glimmer 30B	1	0	1

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

Direct0 labelsNone

Paraphrase1 labelNone

Comparative8 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative6 labels1not counted in share

First choiceAlternativeMentionNegative15 labels in all, every segment counted; 0 of the 1 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.

“You likely need a dedicated engine like dbt tests, Soda, or Elementary instead.” Qwen 3.7 Flash · Data observability · negative prompt · alternative

“Established players with clear pricing: dbt tests (for transformation layer)” Kimi K2 · Data observability · negative prompt · alternative

“Native testing built into your transformation layer” Kimi K2 · Data observability · paraphrase prompt · alternative

“For dbt-native monitoring, use Elementary.” Muse Glimmer 30B · Data observability · comparative 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.

No model argued against it.

Named alongside

The products named in the same answers as dbt tests, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and dbt tests was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Great Expectations15 of 154Not among the top eight

Monte Carlo14 of 152Not among the top eight

Bigeye13 of 150Not among the top eight

Soda10 of 153Not among the top eight

Metaplane9 of 153Not among the top eight

Elementary7 of 151Not among the top eight

Anomalo7 of 150Not among the top eight

Soda Core5 of 152Not among the top eight

Collibra Data Quality & Observability5 of 150Not among the top eight

Acceldata4 of 150Not among the top eight

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 dbt tests. 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 15 of the 15 answers that named dbt tests and are not a share of its labels.

Domains cited

atlan.com10

g2.com8

guideflow.com6

learn.g2.com6

datamation.com5

metaplane.dev5

airbyte.com4

checkthat.ai4

decube.io4

devopsschool.com4

No domain is on file for dbt tests, so its own site is not marked.

Pages cited

atlan.com/know/data-observability-tools8

learn.g2.com/best-data-observability-software6

g2.com/categories/data-observability5

guideflow.com/blog/data-observability-software5

datamation.com/big-data/data-observability-tools4

devopsschool.com/blog/top-10-data-observability-tools-features-pros-cons-comparison4

digna.ai/data-quality-monitoring-tools4

metaplane.dev/blog/best-data-quality-tools4

Pages are listed as the models cited them.

Search and answers

Where dbt tests stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: not counted (“dbt tests”)
AI search demand for its name, est.: 30 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 26 of 110 in data observability

Segment leader

31%

Metaplane

First choices: 0 across its categories
Named in: 15 answers
Its own site cited: No site on file to match

Search figures are US estimates from DataForSEO, read October 5, 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 dbt tests

What the judge wrote, as written, with how often. The vendor table decides that these count as dbt tests; a claim can dispute any of them.

dbt Tests 2

Follow dbt tests

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.

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 dbt tests'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 dbt tests, 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 dbt tests by email, built from the raw record of the edition. It shows:

where dbt tests 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 dbt tests, 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.