Microsoft · 3 categories · RankedMicrosoft SQL Server
29Judge labels
1First choices
8Negative labels
13 / 14Models named it
3Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Best standing
2% in Data masking for small business buyers
Rank 27 of 140 in the mid-market standingcriticized challenger
0 of 14 models made it the first choice on the direct prompt; 30% of its 10 labels there were negative.
What the models named instead of Microsoft SQL Server →By buyer segmentRead the same way at every buyer size.
Small business8 of 152
2%13 labels
accepted challenger
Mid-market27 of 140
0%10 labels
criticized challenger
Enterprise90 of 126
0%2 labels
under the label threshold
In data masking · 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 Microsoft SQL Server 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 masking and test data management | Data platform | 0% | 27 of 140 | 30% | 10 | criticized challenger | |
| Time series databases | Data platform | 0% | 61 of 66 | 100% | 2 | under 10 labels · led by TimescaleDB at 63% | |
| Managed relational databases | Data platform | 0% | 35 of 82 | 0% | 1 | under 10 labels · led by Amazon RDS at 45% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
This is the first edition on this tier, so no move can be computed for Microsoft SQL Server 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 Microsoft SQL Server 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 Microsoft SQL Server 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 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 1 | 1 |
| Perplexity Sonar | 0 | 0 | 0 | 1 | 1 |
| Grok 4.20 | 0 | 1 | 0 | 0 | 1 |
| Mistral Small | 0 | 0 | 0 | 2 | 2 |
| DeepSeek V4 Flash | 0 | 1 | 0 | 0 | 1 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 1 | 0 | 0 | 1 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 1 | 0 | 1 | 2 |
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
Direct7 labelsNone
Paraphrase1 labelNone
Comparative8 labelsNone
Budget-constrained7 labels1
Scale-constrained1 labelNone
Negative5 labelsNone
First choiceAlternativeMentionNegative29 labels in all, every segment counted; 1 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.
“Built-in data masking for Azure SQL databases (cost-effective if you're already in the Azure ecosystem)” MiniMax M2.5 · Data masking · budget prompt · alternative
“if your business already depends on Microsoft tooling, SQL Server skills, or .NET-heavy legacy systems” GPT-5.4 mini · Managed databases · paraphrase prompt · alternative
“Already on SQL Server / Azure: Use native Dynamic Data Masking to mask without adding tool cost.” Muse Glimmer 30B · Data masking · budget prompt · alternative
“Best "Built-In" Option ... Limitation: Only works within SQL Server/Azure environments” DeepSeek V4 Flash · Data masking · 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.
“they are not optimized for large volumes... making them poor choices for serious time series workloads” Mistral Small · Time series DBs · negative prompt · hard negative
“Many major database engines (e.g., SQL Server, Oracle, Snowflake) offer native, built-in Dynamic Data Masking (DDM) out of the box. While convenient, relying on these as your primary defense is highly risky.” Gemini 3.5 Flash · Data masking · negative prompt · soft negative
“DDM is often criticized for limited functionality outside Microsoft ecosystems and for not providing comprehensive compliance templates out of the box” Mistral Small · Data masking · negative prompt · soft negative
“PostgreSQL, MySQL, and SQL Server are fine for *small-scale* time-series workloads, but ... they become a poor fit” Perplexity Sonar · Time series DBs · negative prompt · soft negative
Named alongside
The products named in the same answers as Microsoft SQL Server, over the 29 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Microsoft SQL Server was named but was not.ShowHide
Named alongside
The products named in the same answers as Microsoft SQL Server, over the 29 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Microsoft SQL Server 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 Microsoft SQL Server. 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 29 of the 29 answers that named Microsoft SQL Server and are not a share of its labels.
Domains cited
ovaledge.com22
checkthat.ai14
hevodata.com13
iri.com13
softwaretestinghelp.com13
outsourceaccelerator.com12
sourceforge.net12
atlan.com11
thectoclub.com10
g2.com9
129 of the 129 domain citations in answers naming Microsoft SQL Server came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Microsoft SQL Server stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Microsoft SQL Server stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 14,800 a month (“microsoft sql server”)
- AI search demand for its name, est.
- 1,331 a month
- Its own site
- It sits on Microsoft's site (microsoft.com), so there are no site figures for it alone
In answers
This editionShare of first choices
0%
rank 27 of 140 in data masking
Segment leader
17%
DATPROF
- First choices
- 1 across its categories
- Named in
- 29 answers
- Its own site cited
- in 29 of the answers that named it
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 Microsoft SQL Server
What the judge wrote, as written, with how often. The vendor table decides that these count as Microsoft SQL Server; a claim can dispute any of them.
SQL Server 3Microsoft SQL Server / Azure SQL Dynamic Data Masking 2Microsoft SQL Server and Azure SQL DDM 2Microsoft Azure 1Microsoft SQL Server / Azure SQL 1Microsoft SQL Server / Azure SQL Dynamic Data Masking (DDM) 1Microsoft SQL Server and Azure SQL Dynamic Data Masking 1Microsoft SQL Server and Azure SQL Dynamic Data Masking (DDM) 1
Follow Microsoft SQL Server
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
Microsoft is the company behind Microsoft SQL Server.ShowHide
The company
Microsoft is the company behind Microsoft SQL Server.
ShowHideOn record
Company records- Also from Microsoft
- Microsoft 365, Microsoft 365 Admin Center, Microsoft 365 Administration, Microsoft 365 Backup, Microsoft 365 Compliance Center, Microsoft 365 Copilot, Microsoft 365 Copilot Chat, Microsoft 365 DSC and 164 more
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 Microsoft SQL Server'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 Microsoft SQL Server, 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 Microsoft SQL Server by email, built from the raw record of the edition. It shows:
- where Microsoft SQL Server 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 Microsoft SQL Server, 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.