One of fourteen models named Soda first on the direct prompt; zero named Great Expectations. Both were named by all fourteen models and Soda carries 42 labels and Great Expectations 37, so the shares are not directly comparable.
Named in one category this edition.
Named in two 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 quality and observability page.
Across every category in the October 2026 Edition, Soda and Great Expectations were named in the same answer fifty-nine times, of the 106 answers naming Soda and the 92 naming Great Expectations. In those answers Great Expectations took the first choice one time and Soda fourteen.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | ||||||
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Why be cautious: if you plan to stay on Soda Core open-source, assess ongoing support and feature parity; Soda Cloud pricing and roadmap are not self-serve” Muse Glimmer 30B · negative prompt · soft negative
“License change risk... Not full observability... Limited out-of-the-box metrics.” DeepSeek V4 Flash · negative prompt · soft negative
“Soda might require more upfront effort to configure tests” Claude Haiku 4.5 · negative prompt · soft negative
“Soda is often the better default because mid-sized teams usually benefit from faster adoption and built-in observability” GPT-5.4 mini · paraphrase prompt · first choice
“I'd shortlist Soda. It offers checks and monitoring across common warehouses and databases” GPT-6 Luna · paraphrase prompt · first choice
“best value choice is usually Great Expectations (GX Core) or Soda Free/open-source first” GPT-5.4 mini · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Data Quality Platforms to Avoid or Be Cautious About ... Great Expectations (OSS Version) ... Best avoided if: You need real-time monitoring, have large datasets” GLM 4.7 FlashX · negative prompt · hard negative
“Great Expectations is widely criticized in the data engineering community for being overly complex, heavy, and difficult to configure.” Gemini 3.5 Flash · negative prompt · soft negative
“it avoids both the enterprise pricing overhead of Monte Carlo and the DIY complexity of open-source options like Great Expectations” DeepSeek V4 Flash · direct prompt · soft negative
“### 1. Great Expectations — Open‑Source Framework ... Pros: Free, highly customizable, widely adopted” GLM 4.7 FlashX · comparative prompt · first choice
“Great Expectations and Soda Core lead for data engineering teams that embed validation in CI/CD pipelines.” Muse Glimmer 30B · comparative prompt · first choice
“best value choice is usually Great Expectations (GX Core) or Soda Free/open-source first” GPT-5.4 mini · budget 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.