Embedded analytics · October 2026 Edition
GoodData vs Apache Superset
Zero of fourteen models named GoodData first on the direct prompt; zero named Apache Superset. GoodData was named by seven of the fourteen models and Apache Superset by nine and GoodData carries 15 labels and Apache Superset 10, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category this edition.
First-choice share2%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate27%20%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#7#8A position in a field of 19; printed, not drawn.
Labels1510A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, GoodData reading right to left. Rank and label count are printed, not drawn.Sisense was named alongside these two in eight of the fourteen direct answers. Metabase vs GoodData · Metabase vs Apache Superset · Sisense vs GoodData
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 embedded analytics page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
GoodDataFirst choices, of fourteen modelsApache Superset
Direct00
Paraphrase00
Comparative20
Budget-constrained011 against GoodData · 2 against Apache Superset
Scale-constrained10
Negative003 against GoodData
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 GoodData and Apache Superset 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 4.1 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 | | |
GoodData Apache Superset first choice named as an alternative argued againstblank: not namedEach cell is one answer, GoodData on the left and Apache Superset on the right.The direct prompt
The plain question, one answer per model, grouped by where GoodData and Apache Superset stood in it.
Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.DeepSeek V4 FlashLuzmo alternatives: GoodData, Sisense
Neither was named
13 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Sisense alternatives: Holistics, Looker Embedded, Metabase, Power BI Embedded
GPT-5.4 miniSisense alternatives: Looker, Power BI Embedded, ThoughtSpot Embedded
Gemini 3.5 FlashOmni alternatives: Embeddable, Luzmo, Metabase, Qrvey
Perplexity SonarThoughtSpot Embedded alternatives: Cube, Looker, Zoho Analytics
Grok 4.1 FastReveal BI alternatives: Bold BI, Domo Everywhere, Power BI Embedded, Tableau, Zoho Analytics
Mistral SmallExplo, Sisense alternatives: Microsoft Power BI Embedded, Tableau Embedded Analytics
Llama 4 MaverickReveal BI alternatives: Cube.dev, Omni.co, Thinklytics Insights, Zoho
Qwen 3.7 FlashSisense alternatives: Looker, Microsoft Power BI Embedded, ThoughtSpot Embedded
Kimi K2Explo alternatives: Looker, Metabase, Power BI Embedded, Preset
GLM 4.7 FlashXMetabase alternatives: Looker, ThoughtSpot Embedded
MiniMax M2.5Microsoft Power BI Embedded alternatives: Cube, Explo, Grow, Looker, Metabase, Sisense, Tableau Embedded Analytics, ThoughtSpot Embedded
GPT-6 LunaMetabase alternatives: Looker Embed, Sisense, ThoughtSpot Embedded
Muse Glimmer 30BSisense alternatives: Reveal BI, Toucan
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
Level: the same share of first choices.
GoodData2%#10 of 17Apache Superset2%#– of 17Mid-marketThe figures above
Level: the same share of first choices.
GoodData2%#7 of 19Apache Superset2%#8 of 19Enterprise
GoodData leads by sixteen points.
GoodData16%#1 of 15Apache Superset0%#– of 15What the models said about GoodData
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid: Looker, Domo, ThoughtSpot, and GoodData if budget is your primary constraint” DeepSeek V4 Flash · budget prompt · hard negative
“Don't use: GoodData (complexity, pricing, proprietary language)” DeepSeek V4 Flash · negative prompt · hard negative
“Steep learning curve (proprietary MAQL language); per-workspace pricing scales poorly for multi-tenant” Grok 4.1 Fast · negative prompt · soft negative
“Choose GoodData/Looker if you are building a software product (SaaS) and need the analytics to look like part of the app itself.” Qwen 3.7 Flash · comparative prompt · first choice
“platforms like Sisense, GoodData, ThoughtSpot, and Explo were purpose-built for that use case” DeepSeek V4 Flash · comparative prompt · first choice
“Top for Scalability: GoodData, ThoughtSpot (strong multi-tenant/AI).” Grok 4.1 Fast · scale prompt · first choice
What the models said about Apache Superset
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“free options, but embedding typically requires paid tiers or significant engineering work to white-label properly” DeepSeek V4 Flash · budget prompt · soft negative
“it has a steeper learning curve to deploy and configure than Metabase” Gemini 3.5 Flash · budget prompt · soft negative
“If you hit their pricing limits and have engineering capacity, move to Apache Superset.” Qwen 3.7 Flash · budget prompt · first choice
“Apache Superset is the lower-license-cost alternative” GPT-6 Luna · budget prompt · alternative
“Apache Superset is a free SQL-native alternative” Muse Glimmer 30B · budget prompt · alternative
Also compared
Metabase vs GoodDataMetabase vs Apache SupersetSisense vs GoodDataSisense vs Apache SupersetLuzmo vs GoodDataLuzmo vs Apache SupersetExplo vs GoodDataExplo vs Apache SupersetThoughtSpot Embedded vs GoodDataThoughtSpot Embedded vs Apache SupersetCube vs GoodDataCube vs Apache SupersetAll twenty-eight head-to-head pages and the full embedded analytics 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.