GTM AI Index

Index › Vendors › Databricks Lakehouse · September 2026 Edition

2 categories · Named, not ranked

Databricks Lakehouse

6Judge labels

0First choices

0Negative labels

4 of 12Models named it

2Categories

September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.

Standing

3 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Databricks Lakehouse was named 3 times in DMP and 1 other category, where Segment led with 18%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market53 of 183

under the label threshold

Enterprise36 of 174

under the label threshold

In dmp · 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 Databricks Lakehouse 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
Data management platforms	GTM data and infrastructure	0%	53 of 183	0%	2	under 10 labels · led by Segment at 18%
Customer intelligence and data science	GTM data and infrastructure	0%	96 of 158	0%	1	under 10 labels · led by Google Analytics 4 at 16%

Movement

This is the first edition on this tier, so no move can be computed for Databricks Lakehouse yet. The next is due October 1, 2026. 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 Databricks Lakehouse across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

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

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

Paraphrase0 labelsNone

Comparative5 labels1not counted in share

Budget-constrained0 labelsNone

Scale-constrained1 labelNone

Negative0 labelsNone

First choiceAlternativeMentionNegative6 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.

“Strong for data engineering, ML, and unifying lake + warehouse workloads.” GPT-5.4 mini · DMP · comparative prompt · alternative

“Best for AI/ML use cases with Spark-based engineering” Mistral Small · DMP · 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 Databricks Lakehouse, over the 6 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Databricks Lakehouse was named but was not.

ProductSame answerTook the first choice insteadHead to head

BigQuery4 of 60Not in the top three

Informatica Intelligent Data Management Cloud3 of 61Not in the top three

Snowflake Data Cloud3 of 61Not in the top three

Collibra3 of 60Not in the top three

Fivetran3 of 60Not in the top three

Microsoft Fabric3 of 60Not in the top three

Microsoft Purview3 of 60Not in the top three

Segment3 of 60Not in the top three

Snowflake2 of 61Not in the top three

Alation2 of 60Not 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 Databricks Lakehouse. 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 1 of the 6 answers that named Databricks Lakehouse and are not a share of its labels.

Domains cited

getcensus.com1

help.salesforce.com1

hightouch.com1

snowflake.com1

Four of the four domain citations in answers naming Databricks Lakehouse came from somebody else's page.

Pages cited

getcensus.com/hubfs/snowplow_census_modern_data_stack_ebook_final.pdf1

help.salesforce.com/s/articleView1

hightouch.com/blog/terradata-hightouch-integration1

hightouch.com/docs/getting-started/concepts1

hightouch.com/platform/reverse-etl1

snowflake.com/en/solutions/departments/marketing1

Pages are listed as the models cited them.

Names read as Databricks Lakehouse

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

Databricks Lakehouse Platform 1

The company

Databricks is the company behind Databricks Lakehouse.

Website: databricks.com
Headquarters: San Francisco, United States
Founded: 2013
Employees: about 4,000 (2022)

From Wikidata, 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 Databricks Lakehouse'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 Databricks Lakehouse, 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 databricks.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.