Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 152 → 128 of 161
2 categories · RankedDatabricks Lakehouse
36Judge labels
0First choices
3Negative labels
14 / 14Models named it
2Categories
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
0% in DMP for mid-market buyers
Rank 21 of 159 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 0% of its 14 labels there were negative.
What the models named instead of Databricks Lakehouse →By buyer segmentRead the same way at every buyer size.
Small business135 of 171
0%4 labels
under the label threshold
Mid-market21 of 159
0%14 labels
accepted challenger
Enterprise23 of 151
0%14 labels
accepted challenger
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 | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data management platforms | GTM data and infrastructure | 0% | 21 of 159 | 0% | 14 | accepted challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data clean rooms | GTM data and infrastructure | 0% | 34 of 100 | 0% | 1 | under 10 labels · led by Snowflake Data Clean Rooms at 19% |
Movement
Since September 2026, Databricks Lakehouse held within the floor in all two categories: no change cleared 11 points.
Best category · DMP · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 29 → 18 of 150
Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 25 → 20 of 137
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| DMP | 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 29 → 21 of 159 |
| Data clean rooms | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 34 of 100, unchanged |
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 Databricks Lakehouse 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 Databricks Lakehouse 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 | 0 | 1 | 0 | 0 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 1 | 0 | 1 | 0 | 2 |
| Perplexity Sonar | 0 | 0 | 1 | 0 | 1 |
| Grok 4.20 | 0 | 1 | 1 | 0 | 2 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 2 | 0 | 0 | 2 |
| Llama 4 Maverick | 0 | 0 | 1 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 2 | 0 | 0 | 2 |
| Kimi K2 | 1 | 0 | 0 | 0 | 1 |
| GLM 4.7 FlashX | 1 | 0 | 0 | 0 | 1 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 1 | 0 | 1 |
| Muse Glimmer 30B | 0 | 1 | 0 | 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
Paraphrase3 labelsNone
Comparative25 labels6not counted in share
Budget-constrained1 labelNone
Scale-constrained0 labelsNone
Negative7 labels1not counted in share
First choiceAlternativeMentionNegative36 labels in all, every segment counted; 0 of the 7 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.
“Snowflake, Microsoft Fabric, and Databricks are the leading "modern" warehouses/lakehouses” GLM 4.7 FlashX · DMP · comparative prompt · first choice
“Pick Databricks if ML/AI, data engineering, and flexibility are your top priorities” Kimi K2 · DMP · comparative prompt · first choice
“Native Spark environment optimized for Python/R and machine learning workloads.” Gemini 3.5 Flash · DMP · comparative prompt · first choice
“Choose Databricks if your organization relies heavily on Machine Learning, AI, and massive unstructured datasets” Qwen 3.7 Flash · 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 36 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.ShowHide
Named alongside
The products named in the same answers as Databricks Lakehouse, over the 36 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.
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 Databricks Lakehouse. 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 33 of the 36 answers that named Databricks Lakehouse and are not a share of its labels.
Domains cited
fortegrp.com14
improvado.io14
g2.com10
blog.hubspot.com9
databricks.comYour site9
fivetran.com9
blog.panoply.io8
doit.software8
domo.com8
estuary.dev8
Eighty-eight of the ninety-seven domain citations in answers naming Databricks Lakehouse came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
databricks.com is not in Google's top ten for any of the category's searches. In the answers, Databricks Lakehouse takes 0% of first choices and Segment takes 37%.ShowHide
Search and answers
databricks.com is not in Google's top ten for any of the category's searches. In the answers, Databricks Lakehouse takes 0% of first choices and Segment takes 37%.
ShowHideIn search
Google, US estimatesPosition for “data management platform for audiences”
–
not in the top ten
Position for “best data management platform for audiences”
–
not in the top ten
- Searches for its name, Google
- 1,000 a month (“databricks lakehouse”)
- AI search demand for its name, est.
- 225 a month
- Organic visits to its site
- about 689,756 a month
- Searches its site ranks for
- 43,327 · 6,682 in the top three
- Sites linking to it
- 33,328
- Paid Google search
- 33 searches its ads show for, about 570 clicks and $34,664 a month (estimate)
In answers
This editionShare of first choices
0%
rank 21 of 159 in DMP
Segment leader
37%
Segment
- First choices
- 0 across its categories
- Named in
- 36 answers
- Its own site cited
- in 33 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.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on databricks.com
24,115
subdomains included
Content
6,867
counted in the table below
Documentation
6,978
Product · Integration
243 · 13
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 3,030 | 10 | 2026-09-28 | CDP | |
| Conference or event | 2,766 | 0 | 2026-06-15 | CDP | |
| Report or ebook | 473 | 0 | 2023-06-01 | CDP | |
| Webinar or virtual event | 277 | 0 | 2020-08-01 | ||
| Glossary or explainer | 232 | 0 | 2020-01-01 | CDP | |
| Comparison | 41 | 0 | 2022-03-01 | ||
| Case study | 39 | 0 | 2019-02-01 | ||
| News or press | 6 | 0 | 2021-07-01 | ||
| Podcast or video | 2 | 0 | 2021-04-01 | ||
| Template or tool | 1 | undated |
Most recent
- 2026-09-28How databricks rolls out frontier models 14000 employees day 1 blog
- 2026-09-28Lakebase search state art full text and vector search postgres blog
- 2026-09-28Manufacturing data and ai connecting product value chain blog
- 2026-09-28How roll out genie one step step enterprise playbook blog
- 2026-09-28Helping marketing data engineering same word different meaning blog
- 2026-09-25Data dialogue how sp global energy made its structured data estate conversational databricks blog
Events in person
Last twelve months
- October 1, 2026Panel: How financial institutions are governing AI in financial crime operationsMiami Beach Convention Center, Miami Beach, United States · spoke
- September 28, 2026 to October 1, 2026Databricks at SIBOS 2026 — Booth AgendaMiami Beach Convention Center, Miami Beach, United States · exhibited
- June 25, 2026Panel: The CMO Hot SeatBasis Oasis · spoke
- June 23, 2026Horizon and Newton Research Breakfast Panel — The Open TableUTA Beach, Cannes, France · sponsored
- June 23, 2026Databricks x AWS Executive Roundtable — Creativity at Scale: The Agentic AI Revolution in MarketingCannelle Restaurant, Cannes, France · hosted
- June 23, 2026Female Quotient Reception at FQ Beach — Above The Croisette: A Cocktail Hour for Marketing LeadersFQ Beach · hosted
- June 22, 2026 to June 26, 2026Databricks at Cannes LionsHotel Martinez, Cannes, France · hosted
- June 22, 2026Fox Advertising x Databricks Panel — The CMO's Outlook: Customer Context and the Future of AdvertisingCary Grant Suite, Carlton Hotel, Cannes, France · hosted
- June 17, 2026Telecommunications Industry ForumMarriott Marquis, Yerba Buena Salon 6, San Francisco · took part
- June 15, 2026 to June 18, 2026Data + AI Summit 2026San Francisco · took part
As the event pages on databricks.com state them, read September 28, 2026.
How it is countedHide how it is counted
Every page databricks.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Of its titles that name a category, most name CDP (17); 0 name its categories the models place it in. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
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 12Databricks (Lakehouse) 1Databricks Lakehouse (Clean Room Features) 1Databricks Lakehouse Platform 1
Follow Databricks Lakehouse
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
Databricks is the company behind Databricks Lakehouse.ShowHide
The company
Databricks is the company behind Databricks Lakehouse.
ShowHideOn record
Wikidata- Website
- databricks.com
- Headquarters
- San Francisco, United States
- Founded
- 2013
- Employees
- about 4,000 (2022)
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
In its own words
Stated by the vendor, not checked- Positioning
- Unify your data, analytics and AI
- For
- Whether you’re a startup or global enterprise, Databricks is built to meet the demands of your business at any scale.
- Price stated
- Usage-based pricing keeps spending in check databricks.com/product/databricks-lakehouse
- Free plan or trial
- Try for free databricks.com/product/data-lakehouse
- Hosting
- AWSAzureGCPSAP
- Not stated on the pages read
- Starting price, integrations, certifications, customers
What Databricks Lakehouse's own pages state, read October 5, 2026: usergroups.databricks.com/open-lakehouse-ai, databricks.com/product/data-lakehouse, databricks.com/glossary/data-lakehouse, databricks.com/product/databricks-lakehouse, databricks.com/product/pricing/databricks-lakehouse. A claimed page can correct any of 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 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.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Databricks Lakehouse by email, built from the raw record of the edition. It shows:
- where Databricks Lakehouse 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 Databricks Lakehouse, 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.