Data quality and observability
Asked as “data observability platform”, and as “data quality tool”, on behalf of a mid-market B2B company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the November 2026 Edition.
Standing · first-choice share
23%
Contested · Monte Carlo 12%
23Metaplane12Monte Carlo10Soda56others
23% of first choices, contested.
Since October 2026▼−8Since October 2026: 31% → 23%, −8 points. Inside the 11-point floor: within noise.Metaplane held the lead, −8 points on 31%, inside the 11-point floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
Metaplane40%Contested▲+9Since October 2026: 31% → 40%, +9 points. Inside the 11-point floor: within noise.Standing →Mid-marketMetaplane23%Contested▼−8Since October 2026: 31% → 23%, −8 points. Inside the 11-point floor: within noise.This pageEnterprise
Monte Carlo43%Clear leader▲+2Since October 2026: 41% → 43%, +2 points. Inside the 11-point floor: within noise.Standing →
Metaplane40%Contested▲+9Since October 2026: 31% → 40%, +9 points. Inside the 11-point floor: within noise.Standing →Mid-marketMetaplane23%Contested▼−8Since October 2026: 31% → 23%, −8 points. Inside the 11-point floor: within noise.This pageEnterpriseMonte Carlo43%Clear leader▲+2Since October 2026: 41% → 43%, +2 points. Inside the 11-point floor: within noise.Standing →The standing
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. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Metaplane23%11%35accepted challenger▼−8Since October 2026: 31% → 23%, −8 points. Inside the 11-point floor: within noise.31% → 23%
Metaplane23%11%35accepted challenger▼−8Since October 2026: 31% → 23%, −8 points. Inside the 11-point floor: within noise.31% → 23%02Monte Carlo12%37%51criticized challenger▲+6Since October 2026: 6% → 12%, +6 points. Inside the 11-point floor: within noise.6% → 12%
Monte Carlo12%37%51criticized challenger▲+6Since October 2026: 6% → 12%, +6 points. Inside the 11-point floor: within noise.6% → 12%03
Soda10%17%46accepted challenger▲+1Since October 2026: 9% → 10%, +1 point. Inside the 11-point floor: within noise.9% → 10%
Soda10%17%46accepted challenger▲+1Since October 2026: 9% → 10%, +1 point. Inside the 11-point floor: within noise.9% → 10%04
Soda Core6%30%10criticized challenger▲+4Since October 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise.2% → 6%
Soda Core6%30%10criticized challenger▲+4Since October 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise.2% → 6%05
Great Expectations4%22%36accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%
Great Expectations4%22%36accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%06
Bigeye4%28%40criticized challenger▲+1Since October 2026: 3% → 4%, +1 point. Inside the 11-point floor: within noise.3% → 4%
Bigeye4%28%40criticized challenger▲+1Since October 2026: 3% → 4%, +1 point. Inside the 11-point floor: within noise.3% → 4%07
Elementary4%6%16accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%
Elementary4%6%16accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%08
Ataccama ONE4%7%15accepted challenger▲+4Since October 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise.0% → 4%
Ataccama ONE4%7%15accepted challenger▲+4Since October 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise.0% → 4%09Datadog Data Observability2%35%20criticized challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise.0% → 2%
Show the five products at 0%, ordered by negative rate
14
Informatica Intelligent Data Management Cloud0%37%19criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Informatica Intelligent Data Management Cloud0%37%19criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%13
Collibra Data Quality & Observability0%31%16criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Collibra Data Quality & Observability0%31%16criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%12
Acceldata0%31%29criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Acceldata0%31%29criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%10
Anomalo0%23%22accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Anomalo0%23%22accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%11
Sifflet0%8%13accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%
Sifflet0%8%13accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. Both editions asked the same fourteen models. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
For buyers
All twenty-eight head-to-head pages: the top eight products, each against each
Metaplane vs Great ExpectationsMetaplane vs BigeyeMetaplane vs ElementaryMetaplane vs Ataccama ONEMonte Carlo vs SodaMonte Carlo vs Soda CoreMonte Carlo vs Great ExpectationsMonte Carlo vs BigeyeMonte Carlo vs ElementaryMonte Carlo vs Ataccama ONESoda 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 ONEGreat Expectations vs BigeyeGreat Expectations vs ElementaryGreat Expectations vs Ataccama ONEBigeye vs ElementaryBigeye vs Ataccama ONEElementary vs Ataccama ONE
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405060708D09
1011121314Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Metaplane23%
Metaplane23%02Monte Carlo12%
Monte Carlo12%03Soda10%
Soda10%04Soda Core6%
Soda Core6%05Great Expectations4%
Great Expectations4%06Bigeye4%
Bigeye4%07Elementary4%
Elementary4%08Ataccama ONE4%
Ataccama ONE4%09Datadog Data Observability2%
10Anomalo0%
Anomalo0%11Sifflet0%
Sifflet0%12Acceldata0%
Acceldata0%13Collibra Data Quality & Observability0%
Collibra Data Quality & Observability0%14Informatica Intelligent Data Management Cloud0%
Informatica Intelligent Data Management Cloud0%What they warned about
One of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Grok 4.20, Mistral Small, DeepSeek V4 Flash, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5, GPT-6 Luna and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Monte Carlo37%
19 of 51 labels negative · 10 of 14 models · 3 hard negative
“What to Avoid ... Monte Carlo | The gold standard for enterprises, but pricing is prohibitive for mid-market” Kimi K2, direct prompt
Bigeye28%
11 of 40 labels negative · 9 of 14 models · 1 hard negative
“Avoid if on a Tight Budget ... Bigeye (~$45K+/year)” DeepSeek V4 Flash, budget prompt
Great Expectations22%
8 of 36 labels negative · 8 of 14 models · 1 hard negative
“Best avoided if you need real-time monitoring or handle large datasets, due to scalability limitations.” Mistral Small, negative prompt
Soda17%
8 of 46 labels negative · 7 of 14 models
“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
What they cite
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted.
Sites the answers cite
74 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 861 links across 236 sites, every framing counted. Ranked by the number of answers carrying the site or page. 20 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
30 answers · 56 citations · 11 models
vendor site · G227 answers · 46 citations · 12 models
vendor site · Atlan19 answers · 22 citations · 10 models
vendor site · Integrate.io16 answers · 16 citations · 8 models
vendor site · Metaplane14 answers · 23 citations · 10 models
vendor site · DataKitchen14 answers · 18 citations · 8 models
vendor site · Monte Carlo13 answers · 18 citations · 9 models
13 answers · 13 citations · 9 models
vendor site · SourceForge12 answers · 13 citations · 8 models
11 answers · 25 citations · 7 models
11 answers · 12 citations · 6 models
11 answers · 11 citations · 7 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
26 answers · 9 models
15 answers · 8 models
13 answers · 9 models
13 answers · 9 models
11 answers · 7 models
10 answers · 6 models
10 answers · 7 models
10 answers · 6 models
8 answers · 3 models
8 answers · 6 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best data observability platform”, “data observability platform”, “data quality and observability platforms”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Metaplane metaplane.dev | 23% | 108 | 590 | 12 | 4,698 | 8 | ||
| Soda soda.io Soda 10%, Soda Core 6%, Soda Data Quality 2% | 17% | 124 | 165,000 | 348,802 | 1,651 | $401 | 9 | |
| Monte Carlo montecarlo.ai | 12% | 160 | 135,000 | 23,412 | 24,468 | |||
| Elementary elementary-data.com Elementary 4%, Elementary OSS 4%, Elementary Data 2% | 10% | 42 | 110,000 | 185,714 | 1,028 | |||
| Great Expectations greatexpectations.io | 4% | 85 | 60,500 | 4,980 | 793 | 0 | ||
| Bigeye bigeye.com | 4% | 111 | 33,100 | 618 | 9,473 | $18,069 | 4 | 5 |
| Ataccama ONE ataccama.com | 4% | 118 | 90 | 0 | 2,552 | 14 | ||
| Grafana Cloud grafana.com | 4% | 183 | 2,400 | 40 | 84,520 | 116 | ||
| Insycle insycle.com | 4% | 14 | 480 | 4 | 13,246 | |||
| New Relic newrelic.com | 4% | 595 | 14,800 | 843 | 83,276 | $412 | 89 |
Google's top ten for the three searches hold 19 sites; 5 of them are among the sites the models cited here (datakitchen.io, datamation.com, g2.com, metaplane.dev, reddit.com). The first result for “best data observability platform” is reddit.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best data observability platform for a mid-market B2B company?”Paraphrase“Which data quality tool would you recommend to a mid-sized B2B company?”Comparative“What are the top data quality and observability platforms and how do they differ?”Budget-constrained“What is the best data observability platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a data observability platform. What should we look at?”Negative“Which data quality and observability platforms should I avoid or be cautious about?”
Claude Haiku 4.5Metaplane, New Relicno first choiceChangedPrizmSite24x7against: Grafana Cloud, Prometheusno first choiceagainst: Bigeye, Collibra Data Quality & Observability, Monte Carlo, Soda
Two alternatives
Monte Carlo, Motadata ObserveOpsSeven alternatives
Acceldata, Bigeye, Collibra Data Quality & Observability, Great Expectations, Monte Carlo, OvalEdge, SodaFour alternatives
Great Expectations, Honeybadger, Soda, ZabbixGPT-5.4 miniMetaplaneSodaChangedMonte CarloGreat Expectations, Soda Coreagainst: Bigeyeno first choiceagainst: Acceldata, Bigeye, Datafold, Great Expectations, IBM Databand, Monte Carlo, Pantomath, Soda, Telmai, Unravel Data
One alternative
Monte CarloTwo alternatives
Collibra Data Quality & Observability, Informatica Intelligent Data Management CloudThree alternatives
Bigeye, Datafold, SodaOne alternative
Datadog Data ObservabilityGemini 3.5 FlashMetaplaneInsycle, MetaplaneChangedagainst: Collibra Data Quality & Observability, Informatica Intelligent Data Management Cloud, Monte CarloMonte CarloElementary Dataagainst: Acceldata, Bigeye, Monte Carlono first choiceagainst: Great Expectations, Soda Core
Three alternatives
Bigeye, Elementary Data, Monte CarloFive alternatives
Atlan, Clay, DemandTools, Elementary Data, SodaSix alternatives
Acceldata, Anomalo, Elementary, Great Expectations, IBM Databand, SodaThree alternatives
Great Expectations, Metaplane, Soda CorePerplexity SonarMetaplaneSodaChangedagainst: Ataccama ONE, Informatica Intelligent Data Management CloudMonte CarloGrafana Cloudagainst: Datadog Data Observabilityno first choiceagainst: Bigeye, Collibra Data Quality & Observability, Datadog Data Observability, Elementary alone, Great Expectations, IBM Databand, Informatica Intelligent Data Management Cloud, Metaplane, Soda
Three alternatives
Elementary, Monte Carlo, SodaTwo alternatives
Great Expectations, ZoomInfo OperationsTen alternatives
Acceldata, Anomalo, Ataccama ONE, Atlan, Bigeye, Collibra Data Quality & Observability, Great Expectations, Informatica Intelligent Data Management Cloud, Metaplane, SodaFour alternatives
Metaplane, New Relic, Prometheus + Grafana, SigNozGrok 4.20Metaplaneagainst: Acceldata, Collibra Data Quality & Observability, Dynatrace, Grafana Cloud, Monte CarloAtaccama ONE, TalendChangedagainst: IBM, IBM InfoSphere, Informatica Intelligent Data Management Cloud, PreciselyInformatica Data Quality, Monte CarloElementaryagainst: Acceldata, Anomalo, Bigeye, Lightup, Monte Carlono first choiceagainst: Elementary, dbt testsagainst: Acceldata, Bigeye, Databand, Datadog Data Observability, Datafold, Dynatrace, Great Expectations, Monte Carlo, Soda
Three alternatives
Bigeye, Datadog Observability, SodaFive alternatives
Anomalo, Astera, Data Ladder, Microsoft Purview, Monte CarloEight alternatives
Acceldata, Anomalo, Ataccama ONE, Bigeye, Elementary, IBM InfoSphere, Oracle, TalendThree alternatives
Great Expectations, OpenMetadata, SodaMistral SmallDatadog Data Observability, New Relicagainst: SolarWinds ObservabilityZoomInfo OperationsOSChangedno first choiceGrafana Cloud, Metaplaneno first choiceagainst: Anomalo, Bigeye, Datadog Data Observability, Great Expectations, Informatica Intelligent Data Management Cloud, Monte Carlo, New Relic
One alternative
IBM InstanaThree alternatives
DemandTools, Melissa, OpenpriseThree alternatives
Elementary, SigNoz, SodaDeepSeek V4 FlashMonte Carloagainst: SodaSoda Data QualityChangedagainst: Monte CarloMonte CarloMetaplaneagainst: Acceldata, Bigeye, Monte Carlo, Siffletno first choiceagainst: Acceldata, Alteryx, Datadog Data Observability, Dynatrace, Great Expectations, Monte Carlo, Soda, YData-Profiling
Two alternatives
Metaplane, SiffletTwo alternatives
Insycle, Melissa Data Quality SuiteNine alternatives
Acceldata, Anomalo, Bigeye, Datafold, Elementary, Great Expectations, Metaplane, Sifflet, SodaThree alternatives
Elementary, Great Expectations, Soda CoreLlama 4 Maverickno first choiceno first choiceHeldAcceldata, Databricks, Pentahono first choiceno first choicenothing named
Two alternatives
DQLabs, Monte CarloQwen 3.7 FlashMonte CarloZoomInfo OperationsOSChangedMonte CarloMetaplaneagainst: Bigeye, Monte CarloMonte Carloagainst: Acceldata, Great Expectations, Informatica Intelligent Data Management Cloud, Monte Carlo, Pandera
Three alternatives
Bigeye, Datadog Data Observability, SodaThree alternatives
Ataccama ONE, DemandTools, Informatica Cloud Data QualityEight alternatives
Bigeye, Collibra Data Quality & Observability, Datafold, Elementary, Great Expectations, Informatica Intelligent Data Management Cloud, Soda, dbt testsTwo alternatives
Elementary Data Observability, SodaThree alternatives
Anomalo, Bigeye, DatafoldKimi K2Metaplaneagainst: Acceldata, Anomalo, Monte CarloAtaccama ONEChangedagainst: Collibra Data Quality & Observability, Informatica Intelligent Data Management Cloud, Oracle, Precisely Trillium, SAPno first choiceElementary OSS, Metaplaneagainst: Soda CoreBigeyeagainst: Monte Carloagainst: Anomalo, Bigeye, Great Expectations, Metaplane, Monte Carlo, Soda
Two alternatives
Bigeye, SodaThree alternatives
Great Expectations, Metaplane, dbt-expectationsTwo alternatives
DataOps TestGen, Great ExpectationsFour alternatives
Anomalo, Elementary, Metaplane, SodaGLM 4.7 FlashXMonte CarloApollo.ioChangedagainst: Lusha, ZoomInfo OperationsAcceldata, Ataccama ONE, Bigeye, Informatica Intelligent Data Management Cloud, Monte Carloagainst: IBMElementary, Soda Coreno first choicenothing named
Two alternatives
Bigeye, SiffletTwo alternatives
Mammoth Analytics, SodaSeven alternatives
Databand, Great Expectations, Oracle, Precisely, SAS, Soda, TalendFive alternatives
DataKitchen TestGen, Great Expectations, Metaplane, Soda, groundcoverMiniMax M2.5Monte Carloagainst: Datadog Data Observability, IBM DatabandInsycleChangedAcceldata, Monte CarloGreat Expectations, Soda CoreMonte Carlonothing named
Four alternatives
Acceldata, DQLabs, Metaplane, SodaTwo alternatives
DemandTools, ZoomInfo OperationsSeven alternatives
Ataccama ONE, Bigeye, Collibra Data Quality & Observability, Databand, Great Expectations, Informatica Intelligent Data Management Cloud, SodaThree alternatives
DataHub, Metaplane, OpenMetadataThree alternatives
Anomalo, Bigeye, SodaGPT-6 LunaSodadbtChangedBigeye, Monte CarloElementary OSSno first choiceagainst: IBM Databand, Metaplane, Monte Carlo
Two alternatives
Datadog Data Observability, Monte CarloOne alternative
SodaFour alternatives
Anomalo, Elementary, Metaplane, SodaOne alternative
SodaMuse Glimmer 30BBigeyeagainst: Datadog Infrastructure Pro, Monte CarloProspeo, SodaChangedMonte Carloagainst: SodaMetaplane, Sodano first choiceagainst: Anomalo, Datadog Data Observability, Metaplane, Monte Carlo, Qualytics, SAS Data Management, Soda Core
Four alternatives
Acceldata, DQLabs, Metaplane, SodaTwo alternatives
DemandTools for AppExchange, ZoomInfo OperationsOSOne alternative
BigeyeFour alternatives
Grafana Cloud, Grafana LGTM Stack, Integrate.io, OpenObserveBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 19:13 | yes | 14 | 9 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 13:54 | yes | 3 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 13:45 | yes | 8 | 23 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 10:54 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:00 | yes | 15 | 15 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 14:11 | yes | 5 | 5 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 19:16 | yes | 24 | 28 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 13:12 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:27 | no | 0 | 28 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 09:11 | yes | 14 | 52 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:09 | yes | 24 | 20 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:55 | yes | 5 | 62 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 09:28 | yes | 3 | 14 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 13:15 | yes | 15 | 28 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:35 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 13:13 | yes | 3 | 6 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 19:42 | yes | 11 | 22 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 10:43 | yes | 10 | 3 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:36 | yes | 5 | 8 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:31 | yes | 5 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 16:22 | yes | 22 | 30 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:04 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:51 | yes | 5 | 17 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 09:44 | yes | 25 | 50 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:14 | yes | 23 | 175 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:34 | yes | 5 | 40 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:25 | yes | 2 | 9 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 11:24 | yes | 12 | 20 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 15:52 | yes | 10 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:04 | yes | 5 | 8 s |
| Comparative | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 11:57 | no | 0 | 15 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 10:04 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:52 | yes | 9 | 14 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:12 | yes | 10 | 10 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 09:18 | yes | 22 | 38 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 11:26 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 19:27 | yes | 10 | 24 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 15:32 | yes | 10 | 41 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 18:46 | yes | 25 | 48 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:17 | yes | 7 | 40 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:31 | yes | 8 | 24 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:59 | yes | 25 | 36 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:03 | yes | 17 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:00 | yes | 2 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 11:38 | yes | 9 | 24 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 16:38 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:38 | yes | 15 | 18 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 14:56 | yes | 5 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:23 | yes | 23 | 27 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:38 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:34 | yes | 5 | 22 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 14:08 | yes | 19 | 43 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 18:20 | yes | 15 | 22 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:06 | yes | 14 | 55 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:51 | yes | 2 | 10 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 08:38 | yes | 15 | 22 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 15:51 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 18:23 | no | 0 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 16:06 | no | 0 | 17 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 12:05 | yes | 10 | 9 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:12 | yes | 5 | 13 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:42 | no | 0 | 5 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:44 | yes | 21 | 33 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:40 | yes | 5 | 4 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:51 | no | 0 | 37 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 19:14 | yes | 15 | 39 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:59 | yes | 14 | 53 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:42 | yes | 10 | 25 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 10:18 | yes | 5 | 16 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 18:49 | yes | 15 | 18 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 18:04 | yes | 19 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:59 | yes | 7 | 9 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 18:32 | no | 0 | 15 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 10:04 | yes | 10 | 5 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:36 | yes | 23 | 16 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 19:18 | yes | 5 | 6 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 14:08 | yes | 24 | 51 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:47 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 17:05 | yes | 10 | 44 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:56 | yes | 25 | 35 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 14:35 | yes | 25 | 19 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 12:49 | no | 0 | 19 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:04 | yes | 3 | 17 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 15:46 | yes | 15 | 24 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
Ataccama read as Ataccama ONE
Collibra read as Collibra Data Quality & Observability
Datadog read as Datadog Data Observability
Datadog (Observability Cloud) read as Datadog Data Observability
Grafana read as Grafana Cloud
IBM Data Observability by Databand read as IBM Databand
Informatica read as Informatica Intelligent Data Management Cloud
ZoomInfo read as ZoomInfo Operations
Unresolved, counted raw
Cleanlist AI
Data Ladder
Databricks Lakehouse Monitoring
Datadog Observability
DemandTools for AppExchange
Elementary Data Observability
Elementary alone
GCP Data Quality
Lusha
Matia
Melissa
Melissa Data
Openrise
Pandera
PipeRider
Qualytics
Rakuten SixthSense Data Observability
SCIKIQ
Sanction/Clearbit
Snowflake Data Quality Monitoring
Soda Data Quality
TestGen Enterprise
Unravel Data
YData-Profiling (formerly Pandas Profiling)
actian.com
eckerson.com
montecarlo.ai
re_data
Discontinued, still offered
No shut-down product was recommended here.