Small business▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
2%from 4% in September 2026
Inside the floor by 9 pointsRank 9 → 12 of 70
Amazon · 2 categories · RankedAmazon Aurora
111Judge labels
24First choices
36Negative 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
26% in Managed databases for enterprise buyers
Rank 2 of 82 in the mid-market standingaccepted challenger
4 of 14 models made it the first choice on the direct prompt; 21% of its 39 labels there were negative.
What the models named instead of Amazon Aurora →By buyer segmentStrongest at enterprise.
Small business13 of 74
1%22 labels
criticized challenger
Mid-market2 of 82
12%39 labels
accepted challenger
Enterprise1 of 92
26%44 labels
criticized challenger
In managed databases · 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 Amazon Aurora 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 |
|---|---|---|---|---|---|---|---|
| Managed relational databases | Data platform | 12% | 2 of 82 | 21% | 39 | accepted challenger | ▲+3Since September 2026: 11% → 14%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| AIOps platforms | IT operations and endpoint | 4% | 10 of 93 | 0% | 2 | under 10 labels · led by New Relic at 17% |
Movement
Since September 2026, Amazon Aurora held within the floor in all two categories: no change cleared 11 points.
Best category · Managed databases · by segment
Mid-market▲+3Since September 2026: 11% → 14%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
14%from 11% in September 2026
Inside the floor by 8 pointsRank 3 → 2 of 72
Enterprise▼−1Since September 2026: 30% → 30%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.
30%from 30% in September 2026
Inside the floor by 10 pointsRank 2 → 1 of 81
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Managed databases | 11% | 14% | ▲+3Since September 2026: 11% → 14%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 3 → 2 of 82 |
| AIOps | 0% | 2% | newNew since September 2026: not ranked then, 2% now. | New this edition | Rank 10 of 93, 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 Amazon Aurora 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 Amazon Aurora 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 | 1 | 1 | 2 |
| GPT-5.4 mini | 1 | 2 | 1 | 0 | 4 |
| Gemini 3.5 Flash | 3 | 0 | 0 | 1 | 4 |
| Perplexity Sonar | 1 | 1 | 0 | 0 | 2 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 1 | 0 | 1 | 1 | 3 |
| DeepSeek V4 Flash | 0 | 0 | 2 | 1 | 3 |
| Llama 4 Maverick | 2 | 1 | 0 | 0 | 3 |
| Qwen 3.7 Flash | 0 | 0 | 2 | 2 | 4 |
| Kimi K2 | 1 | 2 | 0 | 1 | 4 |
| GLM 4.7 FlashX | 2 | 0 | 0 | 0 | 2 |
| MiniMax M2.5 | 1 | 1 | 1 | 0 | 3 |
| GPT-6 Luna | 0 | 1 | 1 | 1 | 3 |
| Muse Glimmer 30B | 2 | 1 | 1 | 0 | 4 |
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 labels12
Paraphrase15 labels8
Comparative24 labels9not counted in share
Budget-constrained12 labels4
Scale-constrained11 labelsNone
Negative29 labelsNone
First choiceAlternativeMentionNegative111 labels in all, every segment counted; 24 of the 33 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.
“a recommended hosted SQL database could be PostgreSQL with a cloud-managed service like AWS Aurora, as it balances capability, cost, and operational simplicity” Llama 4 Maverick · Managed databases · paraphrase prompt · first choice
“Pick AWS RDS/Aurora for broadest engine breadth and ecosystem maturity, and for cloud-native Aurora performance with MySQL/PostgreSQL compatibility.” Muse Glimmer 30B · Managed databases · comparative prompt · first choice
“is Amazon Relational Database Service (RDS) or Amazon Aurora, as they are fully managed relational database services” Llama 4 Maverick · Managed databases · direct prompt · first choice
“Go with Amazon Aurora. Its tight integration with AWS... make it the top performance-tier option on AWS.” Gemini 3.5 Flash · Managed databases · comparative prompt · first choice
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.
“Experts advise caution or avoidance for production environments where stable performance is critical.” Mistral Small · Managed databases · negative prompt · hard negative
“Aurora uses internal optimizations and sometimes proprietary features ... that can make migrating back to standard MySQL/Postgres difficult” Qwen 3.7 Flash · Managed databases · negative prompt · soft negative
“While Aurora is popular, be cautious about: Complex pricing - I/O charges can escalate unpredictably” Kimi K2 · Managed databases · negative prompt · soft negative
“not Aurora unless you have a demonstrated need for its different performance or scaling characteristics” GPT-6 Luna · Managed databases · paraphrase prompt · soft negative
Named alongside
The products named in the same answers as Amazon Aurora, over the 107 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Amazon Aurora was named but was not.ShowHide
Named alongside
The products named in the same answers as Amazon Aurora, over the 107 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Amazon Aurora 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 Amazon Aurora. 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 102 of the 107 answers that named Amazon Aurora and are not a share of its labels.
Domains cited
it-ai-index.com49
g2.com46
digitalocean.com41
northflank.com37
aws.amazon.comYour site32
learn.microsoft.com32
tech-insider.org31
cloud.google.com28
docs.aws.amazon.comYour site25
docs.cloud.google.com20
284 of the 341 domain citations in answers naming Amazon Aurora came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
aws.amazon.com is not in Google's top ten for any of the category's searches. In the answers, Amazon Aurora takes 12% of first choices and Amazon RDS takes 45%.ShowHide
Search and answers
aws.amazon.com is not in Google's top ten for any of the category's searches. In the answers, Amazon Aurora takes 12% of first choices and Amazon RDS takes 45%.
ShowHideIn search
Google, US estimatesPosition for “managed relational database service”
–
not in the top ten
Position for “managed relational database services”
–
not in the top ten
- Searches for its name, Google
- 2,400 a month (“amazon aurora”)
- AI search demand for its name, est.
- 291 a month
- Organic visits to its site
- about 9,238,321 a month
- Searches its site ranks for
- 150,884 · 37,235 in the top three
- Sites linking to it
- 282,981
- Paid Google search
- 22 searches its ads show for, about 942 clicks and $20,476 a month (estimate)
Ads on Google
None found in Google's ad transparency records for the US
In answers
This editionShare of first choices
12%
rank 2 of 82 in managed databases
Segment leader
45%
Amazon RDS
- First choices
- 24 across its categories
- Named in
- 107 answers
- Its own site cited
- in 102 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 aws.amazon.com
280,316
subdomains included
Content
42,799
counted in the table below
Documentation
2,345
Product · Integration
3,213 · 49,021
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 27,117 | undated | API gateways, ETL | ||
| Glossary or explainer | 6,521 | undated | ETL, MFA | ||
| Case study | 2,476 | 0 | 2019-03-01 | WAF, Observability | |
| Webinar or virtual event | 2,057 | 16 | 2026-07-01 | Streaming, API gateways | |
| Comparison | 1,521 | 0 | 2025-09-01 | Object storage, ETL | |
| Conference or event | 1,482 | 0 | 2025-11-01 | Vector databases | |
| Report or ebook | 1,090 | 16 | 2026-09-01 | WAF, NoSQL | |
| Podcast or video | 351 | undated | ETL | ||
| Template or tool | 150 | 0 | 2025-05-01 | ||
| News or press | 34 | undated |
Most recent
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
- 2026-09-01Sagemaker cicd notebook ai manifest report or ebook
Events in person
Last twelve months
- July 2, 2026When AI Agents Pay and Sellers Monetize: Building x402 Apps for Agentic CommerceMoscone West, San Francisco, United States · spoke
- July 2, 2026Harness Engineering: Building the Production Cage for Powerful Domain AgentsMoscone West, San Francisco, United States · spoke
- July 2, 2026Agents That Forge Their Own Tools: Self-Modifying AI in the WildMoscone West, San Francisco, United States · spoke
- July 2, 2026Tell the Robots What You WantMoscone West, San Francisco, United States · spoke
- July 1, 20261,000 Agent Tasks in a Sandbox: What Breaks When LLMs Write and Run CodeMoscone West, San Francisco, United States · spoke
- July 1, 2026The Infinite Context Window Is a Myth: Context Engineering for AI AgentsMoscone West, San Francisco, United States · spoke
- June 30, 2026From AI-Assisted to AI-Native: Building a Frontier Development TeamMoscone West, San Francisco, United States · spoke
- June 29, 2026 to July 2, 2026AWS at AI Engineer World's Fair 2026Moscone West, San Francisco, United States · exhibited
- June 29, 2026Agent Speedrun: Idea → Code → Deploy → Observe → Fix → ShipMoscone West, San Francisco, United States · spoke
- May 20, 2026ZF Friedrichshafen AG: From SAP RISE to Enterprise TransformationPAR1152 Hall 9 Theater, Madrid · spoke
- May 19, 2026 to May 21, 2026SAP Sapphire 2026IFEMA Madrid, Madrid · exhibited
- May 19, 2026AWS Reception at Azotea CibelesAzotea Cibeles, Madrid, Spain · hosted
- May 13, 2026How Mondi AG is transforming SAP Operations with AWS AIPAR1004 Theater 11, Orlando · spoke
- May 12, 2026Tapestry accelerates innovation journey with AWS AI servicesPAR1003 Theater 1, Orlando · spoke
- May 12, 2026AWS Reception at Helena Modern RivieraHelena Modern Riviera, Orlando · hosted
- May 11, 2026 to May 13, 2026SAP Sapphire 2026Orange County Convention Center, Orlando · exhibited
- March 25, 2026OCSF Networking BreakfastIntercontinental San Francisco, San Francisco, US · hosted
- March 25, 2026AWS & CrowdStrike are co-hosting a Customer SoireeThe Mint, San Francisco, US · hosted
- March 24, 2026AWS Network Security EventSan Francisco Loft, San Francisco, US · hosted
- March 23, 2026Detective and Response RoundtableSan Francisco Loft, San Francisco, US · hosted
As the event pages on aws.amazon.com state them, read September 28, 2026.
How it is countedHide how it is counted
Every page aws.amazon.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 ETL (168); 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 28, 2026.
Names read as Amazon Aurora
What the judge wrote, as written, with how often. The vendor table decides that these count as Amazon Aurora; a claim can dispute any of them.
Aurora 5AWS Aurora PostgreSQL 3AWS Aurora 2Amazon Aurora Serverless v2 2Aurora PostgreSQL 2AWS Aurora/MySQL 1AWS RDS/Aurora PostgreSQL 1Amazon Aurora (MySQL/PostgreSQL) 1Amazon Aurora (part of AWS RDS) 1Amazon RDS / Amazon Aurora 1Aurora (by Arvo AI) 1Aurora Serverless v2 1Aurora by Arvo AI 1RDS/Aurora 1
Follow Amazon Aurora
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
Amazon is the company behind Amazon Aurora.ShowHide
The company
Amazon is the company behind Amazon Aurora.
ShowHideOn record
Company recordsIn its own words
Stated by the vendor, not checked- Positioning
- Serverless relational database service for PostgreSQL, MySQL, and DSQL
- Not stated on the pages read
- Who it is for, price, starting price, free plan or trial, integrations, certifications, hosting, customers
What Amazon Aurora's own pages state, read September 28, 2026: aws.amazon.com, aws.amazon.com/pricing, aws.amazon.com/security, aws.amazon.com/products, aws.amazon.com/s3/customers. 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 Amazon Aurora'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 Amazon Aurora, 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 Amazon Aurora by email, built from the raw record of the edition. It shows:
- where Amazon Aurora 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 Amazon Aurora, 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.
Badges
Wins only: a badge exists where Amazon Aurora is ranked in a category's top three this edition. Three sizes, one file each, light and dark; the code is under each.ShowHide
Badges
Wins only: a badge exists where Amazon Aurora is ranked in a category's top three this edition. Three sizes, one file each, light and dark; the code is under each.
ShowHideAmazon Aurora is among the products AI models recommend first in Managed relational databases this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Wide · 320 × 104 Website, beside other badges
Square · 240 × 240 LinkedIn, slides
Compact · 200 × 56 Email signature, footer
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.