Data quality and observability · November 2026 Edition
Soda vs Soda Core
One of fourteen models named Soda first on the direct prompt; zero named Soda Core. Soda was named by fourteen of the fourteen models and Soda Core by eight and Soda carries 46 labels and Soda Core 10, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
First-choice share10%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate17%30%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 14; printed, not drawn.
Labels4610A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Soda reading right to left. Rank and label count are printed, not drawn.Monte Carlo was named alongside these two in nine of the fourteen direct answers. Metaplane vs Soda · Metaplane vs Soda Core · Monte Carlo vs Soda
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
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SodaFirst choices, of fourteen modelsSoda Core
Direct101 against Soda
Paraphrase30
Comparative001 against Soda
Budget-constrained131 against Soda Core
Scale-constrained00
Negative006 against Soda · 2 against Soda Core
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Soda and Soda Core stood in it.
| 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 Soda Core first choice named as an alternative argued againstblank: not namedEach cell is one answer, Soda on the left and Soda Core on the right.The direct prompt
The plain question, one answer per model, grouped by where Soda and Soda Core stood in it.
Soda first, Soda Core not the choice
1 of 14 modelsSoda Core was named in the answer but not as the choice, or not at all.GPT-6 LunaSoda alternatives: Datadog Data Observability, Monte Carlo
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.Perplexity SonarMetaplane alternatives: Elementary, Monte Carlo, Soda
Grok 4.20Metaplane alternatives: Bigeye, Datadog Observability, Soda
Qwen 3.7 FlashMonte Carlo alternatives: Bigeye, Datadog Data Observability, Soda
Kimi K2Metaplane alternatives: Bigeye, Soda
MiniMax M2.5Monte Carlo alternatives: Acceldata, DQLabs, Metaplane, Soda
Muse Glimmer 30BBigeye alternatives: Acceldata, DQLabs, Metaplane, Soda
Neither was named
7 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Metaplane, New Relic alternatives: Monte Carlo, Motadata ObserveOps
GPT-5.4 miniMetaplane alternatives: Monte Carlo
Gemini 3.5 FlashMetaplane alternatives: Bigeye, Elementary Data, Monte Carlo
Mistral SmallDatadog Data Observability, New Relic alternatives: IBM Instana
DeepSeek V4 FlashMonte Carlo alternatives: Metaplane, Sifflet
Llama 4 Maverickno first choice
GLM 4.7 FlashXMonte Carlo alternatives: Bigeye, Sifflet
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
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Mid-marketThe figures above
Enterprise
Level: the same share of first choices.
Soda0%#8 of 15Soda Core0%#– 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 Soda Core
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Open-source data quality engines (like Great Expectations or Soda) ... self-hosting and maintaining them at scale requires significant engineering bandwidth.” Gemini 3.5 Flash · negative prompt · soft negative
“It's fast and flexible, but limited to the command line. There's no UI, alerting, or centralized tracking.” Muse Glimmer 30B · negative prompt · soft negative
“Caution: Per-table pricing can escalate quickly with many tables” Kimi K2 · budget prompt · soft negative
“For most small to mid-sized companies with limited budgets, Soda Core or Elementary would be excellent starting points” GLM 4.7 FlashX · budget prompt · first choice
“Best ultra-budget option: Great Expectations or Soda Core for basic data quality checks” GPT-5.4 mini · budget prompt · first choice
“Start with GX Core or Soda Core for data quality testing” MiniMax M2.5 · budget prompt · first choice
Also compared
Metaplane vs SodaMetaplane vs Soda CoreMonte Carlo vs SodaMonte Carlo vs Soda CoreSoda vs Great ExpectationsSoda vs BigeyeSoda vs ElementarySoda vs Ataccama ONESoda Core vs Great ExpectationsSoda Core vs BigeyeSoda Core vs ElementarySoda Core vs Ataccama ONEAll twenty-eight head-to-head pages and the full data observability standing
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.