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 11 → 45 of 46
Databricks · 2 categories · RankedDatabricks SQL
125Judge labels
0First choices
26Negative labels
14 / 14Models named it
2Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Best standing
0% in Data warehouses for mid-market buyers
Rank 5 of 26 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 12% of its 41 labels there were negative.
What the models named instead of Databricks SQL →By buyer segmentRead the same way at every buyer size.
Small business49 of 49
0%30 labels
criticized challenger
Mid-market5 of 26
0%41 labels
accepted challenger
Enterprise7 of 42
0%52 labels
accepted challenger
In data warehouses · 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 SQL 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 warehouses | Data platform | 0% | 5 of 26 | 12% | 41 | accepted challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data virtualization | Data platform | 0% | 34 of 99 | 0% | 1 | under 10 labels · led by Denodo at 28% |
Movement
Since September 2026, Databricks SQL held within the floor in all two categories: no change cleared 11 points.
Best category · Data warehouses · 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 8 → 5 of 25
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 4 → 7 of 37
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Data warehouses | 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 8 → 5 of 26 |
| Data virtualization | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 34 of 99, 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 SQL 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 SQL 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 | 2 | 0 | 3 |
| GPT-5.4 mini | 0 | 1 | 2 | 0 | 3 |
| Gemini 3.5 Flash | 0 | 0 | 1 | 0 | 1 |
| Perplexity Sonar | 0 | 1 | 0 | 0 | 1 |
| Grok 4.20 | 0 | 2 | 1 | 1 | 4 |
| Mistral Small | 0 | 0 | 1 | 1 | 2 |
| DeepSeek V4 Flash | 1 | 3 | 0 | 2 | 6 |
| Llama 4 Maverick | 0 | 0 | 5 | 0 | 5 |
| Qwen 3.7 Flash | 0 | 1 | 2 | 0 | 3 |
| Kimi K2 | 0 | 1 | 2 | 1 | 4 |
| GLM 4.7 FlashX | 0 | 2 | 0 | 0 | 2 |
| MiniMax M2.5 | 0 | 1 | 1 | 0 | 2 |
| GPT-6 Luna | 0 | 2 | 1 | 0 | 3 |
| Muse Glimmer 30B | 0 | 2 | 1 | 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
Direct20 labelsNone
Paraphrase20 labelsNone
Comparative28 labelsNone
Budget-constrained7 labelsNone
Scale-constrained29 labelsNone
Negative21 labels1not counted in share
First choiceAlternativeMentionNegative125 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.
“If you want the safest picks, look toward open-table-format ecosystems ... or Databricks' lakehouse for its openness” DeepSeek V4 Flash · Data warehouses · negative prompt · first choice
“Your main need is a broader lakehouse platform for data engineering, machine learning, or AI—not just a conventional SQL warehouse.” GPT-6 Luna · Data warehouses · direct prompt · alternative
“Databricks if your needs go beyond warehousing into lakehouse, engineering, ML, and AI” GPT-5.4 mini · Data warehouses · paraphrase prompt · alternative
“Databricks — if you need heavy machine learning/AI workloads alongside analytics” DeepSeek V4 Flash · Data warehouses · scale 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.
“The DBU-based pricing can become unpredictable and expensive for small teams.” DeepSeek V4 Flash · Data warehouses · budget prompt · hard negative
“can lead to vendor lock-in due to its tight integration with cloud ecosystems and proprietary formats” Mistral Small · Data warehouses · negative prompt · soft negative
“higher costs/complexity for pure SQL/BI vs. warehouses. Pricing opacity for mixed workloads.” Grok 4.20 · Data warehouses · negative prompt · soft negative
“Cost overruns and complexity — likely overkill for most mid-market B2B companies.” DeepSeek V4 Flash · Data warehouses · direct prompt · soft negative
Named alongside
The products named in the same answers as Databricks SQL, over the 125 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Databricks SQL was named but was not.ShowHide
Named alongside
The products named in the same answers as Databricks SQL, over the 125 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Databricks SQL 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 SQL. 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 103 of the 125 answers that named Databricks SQL and are not a share of its labels.
Domains cited
ovaledge.com61
fortegrp.com57
clickhouse.com52
fivetran.com40
motherduck.com30
atlan.com27
scnsoft.com27
double.cloud25
aegissofttech.com18
airbyte.com18
355 of the 355 domain citations in answers naming Databricks SQL came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
databricks.com ranks 6 on Google for the category's searches. In the answers, Databricks SQL takes 0% of first choices and Snowflake takes 49%.ShowHide
Search and answers
databricks.com ranks 6 on Google for the category's searches. In the answers, Databricks SQL takes 0% of first choices and Snowflake takes 49%.
ShowHideIn search
Google, US estimatesPosition for “cloud data warehouse”
–
not in the top ten
Position for “cloud data warehouses”
–
not in the top ten
- Searches for its name, Google
- 720 a month (“databricks sql”)
- AI search demand for its name, est.
- 282 a month
- Its company's site
- databricks.com shared with Databricks's other products; the figures are the site's
- 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 5 of 26 in data warehouses
Segment leader
49%
Snowflake
- First choices
- 0 across its categories
- Named in
- 125 answers
- Its own site cited
- in 103 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.
Names read as Databricks SQL
What the judge wrote, as written, with how often. The vendor table decides that these count as Databricks SQL; a claim can dispute any of them.
Databricks 29Databricks (Databricks SQL) 1Databricks SQL / Lakehouse 1Databricks SQL Warehouse 1Databricks SQL Warehouse / Lakehouse 1
Follow Databricks SQL
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.
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The company
Databricks is the company behind Databricks SQL.ShowHide
The company
Databricks is the company behind Databricks SQL.
ShowHideOn record
Company recordsIn its own words
Stated by the vendor, not checked- Positioning
- Learn how to use the API to transfer ownership of a SQL warehouse to a new owner
- For
- Anyone who wants to transfer ownership of a SQL warehouse to another user
- Not stated on the pages read
- Price, starting price, free plan or trial, integrations, certifications, hosting, customers
What Databricks SQL's own pages state, read September 28, 2026: kb.databricks.com/en_US/dbsql/update-the-databricks-sql-warehouse-owner, kb.databricks.com/en_US/dbsql/find-long-running-queries-in-your-sql-warehouse, kb.databricks.com/en_US/dbsql/sql-warehouse-spins-up-despite-no-queries-executed, kb.databricks.com/en_US/dbsql/cannot-customize-apache-spark-config-in-databricks-sql-warehouse, docs.databricks.com/aws/en/sql/dbsql-api-latest. 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 SQL'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 SQL, 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 SQL by email, built from the raw record of the edition. It shows:
- where Databricks SQL 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 SQL, 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.