| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Managed relational databases | Data platform | 2% | 7 of 82 | 20% | 56 | accepted challenger | ▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data warehouses | Data platform | 0% | 9 of 26 | 0% | 5 | under 10 labels · led by Snowflake at 49% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Managed databases | 4% | 2% | ▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 6 → 7 of 82 |
| 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 14 → 9 of 26 |
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
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 2 | 2 | 0 | 4 |
| GPT-5.4 mini | 0 | 4 | 0 | 1 | 5 |
| Gemini 3.5 Flash | 0 | 3 | 1 | 1 | 5 |
| Perplexity Sonar | 1 | 4 | 0 | 1 | 6 |
| Grok 4.20 | 0 | 3 | 2 | 1 | 6 |
| Mistral Small | 0 | 1 | 2 | 1 | 4 |
| DeepSeek V4 Flash | 0 | 3 | 1 | 1 | 5 |
| Llama 4 Maverick | 0 | 1 | 1 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 1 | 2 | 1 | 4 |
| Kimi K2 | 0 | 4 | 0 | 1 | 5 |
| GLM 4.7 FlashX | 0 | 2 | 0 | 1 | 3 |
| MiniMax M2.5 | 1 | 1 | 2 | 1 | 5 |
| GPT-6 Luna | 0 | 0 | 1 | 0 | 1 |
| Muse Glimmer 30B | 0 | 5 | 0 | 1 | 6 |
Verbatim evidence the judge attached to positive labels.
“Azure SQL Database is a fully managed, intelligent relational database service built on the Microsoft SQL Server engine” Perplexity Sonar · Managed databases · comparative prompt · first choice
“Amazon RDS or Azure SQL Database would be the safest bets depending on your existing tech stack” MiniMax M2.5 · Managed databases · paraphrase prompt · first choice
“Best for Microsoft Shops ... Lower first-choice share (4%) in general recommendations, but very strong within Microsoft-centric environments” Kimi K2 · Managed databases · direct prompt · alternative
“Pick Azure SQL family when you need tight Microsoft SQL Server integration, built-in AI-powered tuning and elastic pools.” Muse Glimmer 30B · Managed databases · comparative prompt · alternative
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.
“Azure SQL Database, while generally robust, has resource caps and licensing implications that require careful planning” Mistral Small · Managed databases · negative prompt · soft negative
“Standard Azure SQL Database strips out many legacy features (like SSIS, SQL Agent jobs, and certain system views)” Qwen 3.7 Flash · Managed databases · negative prompt · soft negative
“These are solid managed services, but Azure's own guidance warns not to choose solely by engine compatibility” Perplexity Sonar · Managed databases · negative prompt · soft negative
“the Basic tier can be under $15/month, but be aware of backup storage and HA options that can add cost.” GLM 4.7 FlashX · Managed databases · budget prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 147 of the 159 answers that named Azure SQL Database and are not a share of its labels.
553 of the 553 domain citations in answers naming Azure SQL Database came from somebody else's page.
Pages are listed as the models cited them.
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.
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.
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 Azure SQL Database'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 Azure SQL Database, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Azure SQL Database by email, built from the raw record of the edition. It shows: