Soda vs Elementary
One of fourteen models named Soda first on the direct prompt; zero named Elementary. Soda was named by fourteen of the fourteen models and Elementary by ten and Soda carries 46 labels and Elementary 16, so the shares are not directly comparable.
Named in one category 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 quality and observability page.
By framing
SodaFirst choices, of fourteen modelsElementary
Across every category in the November 2026 Edition, Soda and Elementary were named in the same answer thirty-five times, of the 133 answers naming Soda and the 43 naming Elementary. In those answers Elementary took the first choice three times and Soda eight.
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 | | | | |
Soda Elementary first choice named as an alternative argued againstblank: not namedEach cell is one answer, Soda on the left and Elementary on the right.The direct prompt
Soda first, Elementary not the choice
1 of 14 modelsElementary was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
7 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
Soda0%#8 of 15Elementary0%#– of 15What the models said about Soda
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Learning curve for non-coders (YAML-based checks can feel technical), and it's not always a full end-to-end replacement for broader tools” Grok 4.20 · negative prompt · soft negative
“Soda is a rule-based data quality assertion tool - well-suited for dbt workflows but not a full operational pipeline.” Muse Glimmer 30B · comparative prompt · soft negative
“often praised for flexibility, but you should be cautious if you don't want to own a rules/config-heavy workflow” GPT-5.4 mini · negative prompt · soft negative
“For most mid-sized B2B companies, I'd recommend Soda as the starting point” Perplexity Sonar · paraphrase prompt · first choice
“start with Soda Free or Metaplane free tier, and Integrate.io's 3 free alerts” Muse Glimmer 30B · budget prompt · first choice
“Soda is highlighted as the budget-friendly start for mid-sized orgs” Muse Glimmer 30B · paraphrase prompt · first choice
What the models said about Elementary
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Open-source options like dbt tests or Elementary can be starters but may lack full automation.” Grok 4.20 · scale prompt · soft negative
“Soda Core or Elementary would be excellent starting points” GLM 4.7 FlashX · budget prompt · first choice
“Top Recommendation: Elementary (Open Source, Self-Hosted)” Grok 4.20 · budget prompt · first choice
“Elementary is a popular open-source option that integrates well with dbt projects and is free to use” Mistral Small · budget 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.