IT AI Index

Index › Vendors › Alibaba Cloud AnalyticDB · September 2026 Edition

1 category · Named, not ranked

Alibaba Cloud AnalyticDB

1Judge labels

0First choices

1Negative labels

1 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

1 label, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Alibaba Cloud AnalyticDB was named 1 time in Data warehouses, where Snowflake led with 47%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market37 of 41

under the label threshold

Enterprisenot named

No model named it for this buyer.

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 Alibaba Cloud AnalyticDB 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
Data warehouses	Data platform	0%	37 of 41	100%	1	under 10 labels · led by Snowflake at 47%

Movement

This is the first edition on this tier, so no move can be computed for Alibaba Cloud AnalyticDB yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Alibaba Cloud AnalyticDB across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Negative	Labels
Claude Haiku 4.5	0	0
GPT-5.4 mini	0	0
Gemini 3.5 Flash	0	0
Perplexity Sonar	0	0
Grok 4.1 Fast	0	0
Mistral Small	0	0
DeepSeek V4 Flash	0	0
Llama 4 Maverick	0	0
Qwen 3.7 Flash	0	0
Kimi K2	0	0
GLM 4.7 FlashX	0	0
MiniMax M2.5	1	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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative1 labelNone

First choiceAlternativeMentionNegative1 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.

No positive label carried a quote.

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.

“When to avoid: Unless your operations are primarily in Asia and you need Alibaba integration.” MiniMax M2.5 · Data warehouses · negative prompt · hard negative

Named alongside

The products named in the same answers as Alibaba Cloud AnalyticDB, over the 1 answer that named it. Took the first choice instead counts the answers where the other product was the first choice and Alibaba Cloud AnalyticDB was named but was not.

ProductSame answerTook the first choice insteadHead to head

Amazon Redshift1 of 10Not in the top three

Apache Druid1 of 10Not in the top three

Azure Synapse Analytics1 of 10Not in the top three

ClickHouse Cloud1 of 10Not in the top three

Google BigQuery1 of 10Not in the top three

IBM Db2 Warehouse1 of 10Not in the top three

Oracle Cloud Infrastructure (OCI) Analytic Warehouse1 of 10Not in the top three

Snowflake1 of 10Not in the top three

Starburst1 of 10Not in the top three

A head-to-head page exists where both products are in a category's top three. 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 Alibaba Cloud AnalyticDB. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 1 of the 1 answers that named Alibaba Cloud AnalyticDB and are not a share of its labels.

Domains cited

blog.quest.com1

classicinformatics.com1

dev.to1

materialize.com1

starburst.io1

Five of the five domain citations in answers naming Alibaba Cloud AnalyticDB came from somebody else's page.

Pages cited

blog.quest.com/cloud-data-warehouse-navigating-the-risks-and-challenges-of-adoption1

classicinformatics.com/blog/cloud-data-warehouse1

dev.to/piya__c204c9e90/cloud-data-warehouse-challenges-and-solutions-for-successful-implem1

materialize.com/blog/warehouse-abuse1

starburst.io/blog/vendor-lock-in1

Pages are listed as the models cited 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 Alibaba Cloud AnalyticDB'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 Alibaba Cloud AnalyticDB, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at alibaba.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.