DataHub vs Microsoft Purview
Zero of fourteen models named DataHub first on the direct prompt; zero named Microsoft Purview. Both were named by all fourteen models and DataHub carries 47 labels and Microsoft Purview 42, so the shares are not directly comparable.
Named in three categories this edition.
Named in eleven categories this edition.
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
DataHubFirst choices, of fourteen modelsMicrosoft Purview
Across every category in the November 2026 Edition, DataHub and Microsoft Purview were named in the same answer seventy times, of the 126 answers naming DataHub and the 562 naming Microsoft Purview. In those answers Microsoft Purview took the first choice two times and DataHub six.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | | |
| Grok 4.20 | | | | | | |
| 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
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
9 of 14 modelsThe answer made no first choice from these two in this category.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
DataHub6%#5 of 16Microsoft Purview6%#6 of 16DataHub11%#4 of 16Microsoft Purview3%#5 of 16DataHub6%#5 of 11Microsoft Purview4%#6 of 11What 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.
“Clunky/difficult interface compared to commercial alternatives ... Open-source options (DataHub) viable but require engineering investment” MiniMax M2.5 · negative prompt · soft negative
“Open-source or niche tools (like DataHub, Amundsen, Marquez) Caution level: Low-to-moderate (only if you lack engineering resources)” DeepSeek V4 Flash · negative prompt · soft negative
“plus OpenMetadata or DataHub if you're willing to take on more of the operational and engineering work” GPT-6 Luna · scale prompt · soft negative
“The Heavyweight Champion: DataHub ... is generally considered the most mature and widely adopted open-source data catalog” Qwen 3.7 Flash · budget prompt · first choice
“Mid-market solutions (Atlan, select, DataHub) often fit better than enterprise-only tools (Collibra) at this scale” Kimi K2 · scale prompt · first choice
“Strongest fit for ~500 employees): *Examples:* Atlan, Select Star, Secoda, CastorDoc, DataHub (Cloud/Acryl Data).” Gemini 3.5 Flash · scale 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. Two of two in this category shown.
“Microsoft Purview (in non-Microsoft environments)” Mistral Small · negative prompt · hard negative
“If you are Microsoft 365 / Azure / Fabric first and want governance + security + compliance with minimal overhead: Microsoft Purview Suite for Business Premium.” Muse Glimmer 30B · paraphrase prompt · first choice
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.