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Data catalogs and governance · October 2026 Edition

DataHub vs Microsoft Purview

One of fourteen models named DataHub first on the direct prompt; zero named Microsoft Purview. DataHub was named by twelve of the fourteen models and Microsoft Purview by thirteen and DataHub carries 36 labels and Microsoft Purview 35, so the shares are not directly comparable.

DataHub

accepted challenger

Named in two categories this edition.

Microsoft Purview

accepted challenger

Named in nine categories this edition.

First-choice share7%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#8A position in a field of 15; printed, not drawn.
Labels3635A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, DataHub reading right to left. Rank and label count are printed, not drawn.Atlan was named alongside these two in thirteen of the fourteen direct answers. Atlan vs DataHub · Atlan vs Microsoft Purview · OpenMetadata vs DataHub

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the data catalogs and governance page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DataHubFirst choices, of fourteen modelsMicrosoft Purview
Direct101 against DataHub
Paraphrase01
Comparative00
Budget-constrained30
Scale-constrained002 against DataHub
Negative002 against DataHub · 5 against Microsoft Purview
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where DataHub and Microsoft Purview stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
DataHub Microsoft Purview first choice named as an alternative argued againstblank: not namedEach cell is one answer, DataHub on the left and Microsoft Purview on the right.

The direct prompt

The plain question, one answer per model, grouped by where DataHub and Microsoft Purview stood in it.

DataHub first, Microsoft Purview not the choice

1 of 14 modelsMicrosoft Purview was named in the answer but not as the choice, or not at all.
GPT-5.4 miniDataHub alternatives: Alation, DataGalaxy

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
DeepSeek V4 FlashSecoda alternatives: Atlan, DataHub
Qwen 3.7 FlashAtlan alternatives: AWS DataZone, DataHub, Google Dataplex, OvalEdge, Seceda
MiniMax M2.5Atlan, Secoda alternatives: Alation, Microsoft Purview
GPT-6 LunaAtlan alternatives: Microsoft Purview, OpenMetadata, Secoda

Neither was named

9 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Atlan alternatives: Alation, OvalEdge
Gemini 3.5 FlashSelect Star alternatives: Atlan, Coalesce Catalog, OvalEdge, Secoda
Perplexity SonarAtlan alternatives: Alation, OvalEdge, Select Star
Grok 4.1 FastAtlan alternatives: Alation, OvalEdge, Secoda
Mistral SmallAtlan, OvalEdge
Llama 4 MaverickAtlan
Kimi K2Secoda alternatives: Atlan, OvalEdge, Select Star
GLM 4.7 FlashXAtlan, Secoda, Select Star alternatives: Informatica Intelligent Data Management Cloud, OvalEdge, data.world
Muse Glimmer 30BAtlan alternatives: Alation, OvalEdge

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Microsoft Purview leads by two points.
Microsoft Purview7%#6 of 16
DataHub5%#7 of 16
The full small business standing →
Mid-marketThe figures above
The order flips: DataHub leads at mid-market.
DataHub7%#5 of 15
Microsoft Purview2%#8 of 15
The full mid-market standing →
Enterprise
The order flips: Microsoft Purview leads at enterprise.
Microsoft Purview6%#4 of 11
DataHub0%#8 of 11
The full enterprise standing →

What the models said about DataHub

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“Avoid for Mid-Market: ... open-source like DataHub/Amundsen (free but needs engineering overhead)” Grok 4.1 Fast · direct prompt · hard negative
“Only choose this if you have a dedicated data platform engineer who has the bandwidth to manage and upgrade the infrastructure.” Gemini 3.5 Flash · scale prompt · soft negative
“While open source options like OpenMetadata and DataHub are credible, they require substantial in-house engineering expertise” Mistral Small · negative prompt · soft negative
“likely to be an open-source tool such as Amundsen or DataHub, which are suitable for on-premise environments” Llama 4 Maverick · budget prompt · first choice
“If you have some technical resources, OpenMetadata or DataHub are the best free options.” Mistral Small · budget prompt · first choice
“Best overall low-budget choice: DataHub” GPT-5.4 mini · budget prompt · first choice

What the models said about Microsoft Purview

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.

“user feedback and reviews frequently highlight immense friction, spotty lineage, and high database scanning costs when trying to integrate Purview with non-Microsoft environments” Gemini 3.5 Flash · negative prompt · soft negative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.