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Dashboards and data visualization · October 2026 Edition

Metabase vs Sigma

Zero of fourteen models named Metabase first on the direct prompt; one named Sigma. Metabase was named by thirteen of the fourteen models and Sigma by eight and Metabase carries 31 labels and Sigma 15, so the shares are not directly comparable.

Metabase

accepted challenger

United States. Named in three categories this edition.

Sigma

accepted challenger

By SIGMA COMPUTING, San Francisco. Named in two categories this edition.

First-choice share8%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#6A position in a field of 11; printed, not drawn.
Labels3115A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Metabase reading right to left. Rank and label count are printed, not drawn.Tableau was named alongside these two in thirteen of the fourteen direct answers. Microsoft Power BI vs Metabase · Microsoft Power BI vs Sigma · Looker Studio vs Metabase

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 dashboards and data visualization page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
MetabaseFirst choices, of fourteen modelsSigma
Direct01
Paraphrase00
Comparative00
Budget-constrained40
Scale-constrained00
Negative102 against Metabase
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 Metabase and Sigma stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Metabase Sigma first choice named as an alternative argued againstblank: not namedEach cell is one answer, Metabase on the left and Sigma on the right.

The direct prompt

The plain question, one answer per model, grouped by where Metabase and Sigma stood in it.

Sigma first, Metabase an alternative

1 of 14 modelsMetabase was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashSigma alternatives: Explo, Metabase, Microsoft Power BI, Sisense, Tableau

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Microsoft Power BI, Tableau alternatives: Metabase
DeepSeek V4 FlashMicrosoft Power BI alternatives: Domo, Looker Studio, Sigma, Tableau, ThoughtSpot
Kimi K2Microsoft Power BI alternatives: Sigma, Sisense, Tableau
GPT-6 LunaMicrosoft Power BI alternatives: Looker, Sigma, Tableau

Neither was named

9 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniMicrosoft Power BI alternatives: Looker, Tableau
Perplexity SonarMicrosoft Power BI alternatives: Tableau, Zoho Analytics
Grok 4.1 FastMicrosoft Power BI alternatives: Looker, Tableau, Zoho Analytics
Mistral SmallTableau alternatives: Domo, Microsoft Power BI
Llama 4 Maverickno first choice
Qwen 3.7 FlashMicrosoft Power BI alternatives: Domo, Looker, Tableau, Zoho Analytics
GLM 4.7 FlashXMicrosoft Power BI alternatives: Looker, Qlik Sense, Tableau
MiniMax M2.5Microsoft Power BI alternatives: Domo, Tableau
Muse Glimmer 30BMicrosoft Power BI alternatives: Domo, Looker, Looker Studio, Tableau, ThoughtSpot

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
Metabase leads by nine points.
Metabase9%#4 of 8
Sigma0%#– of 8
The full small business standing →
Mid-marketThe figures above
Metabase leads by six points.
Metabase8%#4 of 11
Sigma2%#6 of 11
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Metabase0%#10 of 10
Sigma0%#7 of 10
The full enterprise standing →

What the models said about Metabase

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.

“3 new zero-day discoveries across Metabase, DataEase, Pentaho, Redash, and Apache Superset” Claude Haiku 4.5 · negative prompt · soft negative
“Open-Source Tools (Avoid without DevOps Support)” Gemini 3.5 Flash · negative prompt · soft negative
“lightweight alternatives like Looker Studio, Metabase, or basic Power BI Pro licenses offer faster value” Qwen 3.7 Flash · negative prompt · first choice
“The Best Overall: Metabase (Open Source)... is widely considered the best free option available.” GLM 4.7 FlashX · budget prompt · first choice
“start with Looker Studio (free) or Metabase (free open-source)” MiniMax M2.5 · budget prompt · first choice

What the models said about Sigma

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“go with Sigma Computing” Gemini 3.5 Flash · direct prompt · first choice
“Choose Sigma if your team lives in Excel, you use Snowflake/Databricks, and you want business users to perform heavy ad-hoc analysis on live data.” Gemini 3.5 Flash · comparative prompt · alternative
“Sisense or Sigma are particularly strong choices due to their embedded analytics capabilities” Kimi K2 · direct prompt · alternative
Also compared

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.