Alation vs Select Star
Zero of fourteen models named Alation first on the direct prompt; zero named Select Star. Alation was named by fourteen of the fourteen models and Select Star by eight and Alation carries 55 labels and Select Star 12, so the shares are not directly comparable.
Named in four categories this edition.
Named in one category 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
AlationFirst choices, of fourteen modelsSelect Star
Across every category in the November 2026 Edition, Alation and Select Star were named in the same answer thirty-seven times, of the 171 answers naming Alation and the 47 naming Select Star. In those answers Select Star took the first choice ten times and Alation two.
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 | | | |
Alation Select Star first choice named as an alternative argued againstblank: not namedEach cell is one answer, Alation on the left and Select Star 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
Select Star16%#3 of 16Alation0%#16 of 16Alation2%#7 of 16Select Star2%#8 of 16Alation10%#3 of 11Select Star0%#– of 11What the models said about Alation
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to Avoid ... Enterprise tools like Collibra, Alation, or Atlan — Excellent products, but typically cost $50K–$200K+ annually.” Kimi K2 · budget prompt · hard negative
“priced at $60K–$198K+/year and works best with a mature governance program (15+ catalogers)” DeepSeek V4 Flash · direct prompt · hard negative
“Avoid expensive enterprise tools like Collibra ($100k+/year), Alation, and Atlan” DeepSeek V4 Flash · budget prompt · hard negative
“If your priority is user adoption and AI-driven discovery, look toward Alation.” Qwen 3.7 Flash · comparative prompt · first choice
“I'd lean Alation when the goal is fast adoption and cross-functional governance” GPT-5.4 mini · paraphrase prompt · first choice
“Generally Positive (The Standards): Alation, Collibra, Fiddler, and Microsoft Purview (with caveats on complexity) are generally viewed as robust” Qwen 3.7 Flash · negative prompt · alternative
What the models said about Select Star
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Strongest fit for ~500 employees): *Examples:* Atlan, Select Star, Secoda, CastorDoc, DataHub” Gemini 3.5 Flash · scale prompt · first choice
“Best for Lean Teams & Quick Time-to-Value: Select Star, Secoda, or CastorDoc” Gemini 3.5 Flash · direct prompt · alternative
“Modern, lightweight SaaS catalogs (e.g., Atlan, Select Star, CastorDoc, Secoda)” Gemini 3.5 Flash · negative prompt · alternative
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.