Secoda vs Select Star
Seven of fourteen models named Secoda first on the direct prompt; zero named Select Star. Secoda was named by thirteen of the fourteen models and Select Star by eight and Secoda carries 26 labels and Select Star 12, so the shares are not directly comparable.
Named in two 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
SecodaFirst choices, of fourteen modelsSelect Star
Across every category in the November 2026 Edition, Secoda and Select Star were named in the same answer thirty-six times, of the 81 answers naming Secoda and the 47 naming Select Star. In those answers Select Star took the first choice four times and Secoda nine.
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 Select Star first choice named as an alternative argued againstblank: not namedEach cell is one answer, Secoda on the left and Select Star on the right.The direct prompt
Secoda first, Select Star an alternative
7 of 14 modelsSelect Star was named in the answer but not as the choice, or not at all.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.Neither was named
3 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 16Select Star16%#3 of 16What 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 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.