Secoda vs Alation
Seven of fourteen models named Secoda first on the direct prompt; zero named Alation. Secoda was named by thirteen of the fourteen models and Alation by fourteen and Secoda carries 26 labels and Alation 55, so the shares are not directly comparable.
Named in two categories this edition.
Named in four 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
SecodaFirst choices, of fourteen modelsAlation
Across every category in the November 2026 Edition, Secoda and Alation were named in the same answer fifty-seven times, of the 81 answers naming Secoda and the 171 naming Alation. In those answers Alation took the first choice three times and Secoda twenty-one.
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 | | | | |
Secoda Alation first choice named as an alternative argued againstblank: not namedEach cell is one answer, Secoda on the left and Alation on the right.The direct prompt
Secoda first, Alation not the choice
7 of 14 modelsAlation was named in the answer but not as the choice, or not at all.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
2 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
Secoda19%#1 of 16Alation0%#16 of 16Alation10%#3 of 11Secoda2%#8 of 11What the models said about Secoda
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“mentioned as being "criticized challengers" or having negative reviews” Llama 4 Maverick · negative prompt · soft negative
“If you want the cheapest, fastest adoption with AI-assisted search, Secoda is the most common mid-market recommendation today.” Muse Glimmer 30B · direct prompt · first choice
“Secoda is frequently highlighted as the strongest recommendation for most mid-market B2B companies” Mistral Small · direct prompt · first choice
“Strongest fit for ~500 employees): *Examples:* Atlan, Select Star, Secoda, CastorDoc, DataHub” Gemini 3.5 Flash · scale prompt · first choice
What 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
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.