IT AI Index
Index Vendors › Google Cloud Dataflow · September 2026 Edition
Google Cloud · 2 categories · Named, not ranked

Google Cloud Dataflow

23Judge labels
0First choices
6Negative labels
8 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.
Standing
6 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Google Cloud Dataflow was named 6 times in ETL and 1 other category, where Airbyte led with 32%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In etl · 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 Google Cloud Dataflow 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.
CategoryFunctionShareRankNegative rateLabelsQuadrant
ETL and ELTData platform0%21 of 660%5under 10 labels · led by Airbyte at 32%
Workflow orchestrationData platform0%33 of 860%1under 10 labels · led by Prefect at 24%

Movement

This is the first edition on this tier, so no move can be computed for Google Cloud Dataflow 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 Google Cloud Dataflow across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.501102
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00101
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00101
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200101
GLM 4.7 FlashX00000
MiniMax M2.501001

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
Paraphrase4 labelsNone
Comparative6 labelsNone
Budget-constrained4 labelsNone
Scale-constrained1 labelNone
Negative5 labelsNone
First choiceAlternativeMentionNegative23 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.

“leverage the free tier credits of AWS Glue, Azure Data Factory, or Google Dataflow” MiniMax M2.5 · ETL · budget prompt · alternative
“Consider this if you're already on Google Cloud and need fully managed infrastructure.” Claude Haiku 4.5 · Orchestration · 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.

No model argued against it.

Named alongside

The products named in the same answers as Google Cloud Dataflow, over the 23 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Google Cloud Dataflow was named but was not.
ProductSame answerTook the first choice insteadHead to head
Fivetran16 of 236Not in the top three
AWS Glue16 of 230Not in the top three
Airbyte13 of 231Not in the top three
Azure Data Factory13 of 230Not in the top three
Talend11 of 231Not in the top three
Apache Airflow10 of 232Not in the top three
Stitch10 of 230Not in the top three
Matillion9 of 230Not in the top three
dbt8 of 230Not in the top three
Apache Kafka5 of 233Not 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 Google Cloud Dataflow. 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 17 of the 23 answers that named Google Cloud Dataflow and are not a share of its labels.

Domains cited

integrate.io10
hevodata.com8
estuary.dev7
airbyte.com5
devopsschool.com4
domo.com4
funnel.io4
g2.com4
guideflow.com4
risingwave.com4

Fifty-four of the fifty-four domain citations in answers naming Google Cloud Dataflow came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Google Cloud Dataflow

What the judge wrote, as written, with how often. The vendor table decides that these count as Google Cloud Dataflow; a claim can dispute any of them.
Google Dataflow 2
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 Google Cloud Dataflow'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 Google Cloud Dataflow, 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 google.dev 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.

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