Small businessnewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 16 of 59, unchanged
Amazon · 1 category · Named, not rankedAmazon DocumentDB
16Judge labels
0First choices
1Negative labels
9 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Standing
5 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Amazon DocumentDB was named 5 times in NoSQL, where MongoDB led with 74%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business16 of 60
0%2 labels
under the label threshold
Mid-market14 of 73
0%5 labels
under the label threshold
Enterprise12 of 54
0%9 labels
under the label threshold
In nosql · 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 DocumentDB 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 |
|---|---|---|---|---|---|---|---|
| NoSQL databases | Data platform | 0% | 14 of 73 | 20% | 5 | under 10 labels · led by MongoDB at 74% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Amazon DocumentDB held within the floor in its one category: no change cleared 11 points.
Best category · NoSQL · 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 15 → 21 of 69
Enterprise▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 2% in September 2026
Inside the floor by 9 pointsRank 8 → 12 of 53
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| NoSQL | 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 15 → 14 of 73 |
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 DocumentDB 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 DocumentDB 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 | 0 | 1 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 1 | 0 | 0 | 1 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 1 | 1 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 1 | 0 | 1 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| 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
Direct3 labelsNone
Paraphrase8 labelsNone
Comparative1 labelNone
Budget-constrained0 labelsNone
Scale-constrained2 labelsNone
Negative2 labelsNone
First choiceAlternativeMentionNegative16 labels in all, every segment counted; 0 of the 0 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.
“Amazon DocumentDB / MongoDB Atlas is the more natural document choice” Muse Glimmer 30B · NoSQL · paraphrase prompt · alternative
“or Amazon DocumentDB (AWS-native)” Grok 4.20 · NoSQL · paraphrase 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.
“Be most cautious about vendor lock-in (DynamoDB, DocumentDB)” DeepSeek V4 Flash · NoSQL · negative prompt · soft negative
Named alongside
The products named in the same answers as Amazon DocumentDB, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Amazon DocumentDB was named but was not.ShowHide
Named alongside
The products named in the same answers as Amazon DocumentDB, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Amazon DocumentDB 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 DocumentDB. 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 13 of the 16 answers that named Amazon DocumentDB and are not a share of its labels.
Domains cited
g2.com6
mongodb.com6
docs.aws.amazon.comYour site4
redis.io4
scylladb.com4
slashdot.org4
sourceforge.net4
aerospike.com3
aws.amazon.comYour site3
db-engines.com3
Thirty-four of the forty-one domain citations in answers naming Amazon DocumentDB came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Amazon DocumentDB stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Amazon DocumentDB stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 480 a month (“amazon documentdb”)
- AI search demand for its name, est.
- 32 a month
- Its own site
- It sits on Amazon's site (amazon.com), so there are no site figures for it alone
In answers
This editionShare of first choices
0%
rank 14 of 73 in nosql
Segment leader
74%
MongoDB
- First choices
- 0 across its categories
- Named in
- 16 answers
- Its own site cited
- in 13 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 Amazon DocumentDB
What the judge wrote, as written, with how often. The vendor table decides that these count as Amazon DocumentDB; a claim can dispute any of them.
AWS DocumentDB 1DocumentDB 1
Follow Amazon DocumentDB
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 DocumentDB.ShowHide
The company
Amazon is the company behind Amazon DocumentDB.
ShowHideOn record
Company records- Also from Amazon
- Amazon API Gateway, Amazon API Gateway HTTP APIs, Amazon AppStream 2.0, Amazon Athena, Amazon Athena Federated Query, Amazon Aurora, Amazon Aurora Serverless, Amazon Bedrock and 46 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 Amazon DocumentDB'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 DocumentDB, 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 DocumentDB by email, built from the raw record of the edition. It shows:
- where Amazon DocumentDB 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 DocumentDB, 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.