# Trino vs Starburst Galaxy: which do AI models recommend for data virtualization, October 2026

IT AI Recommendation Index, October 2026 Edition, Data virtualization. Zero of fourteen models named Trino first on the direct prompt; two named Starburst Galaxy. Page: https://it-ai-index.com/it-data/data-virtualization/trino-vs-starburst-galaxy/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Trino | 15% | #2 of 10 | 17% | 18 | 10 of 14 |
| Starburst Galaxy | 13% | #3 of 10 | 0% | 13 | 9 of 14 |

## The direct prompt, model by model

- Qwen 3.7 Flash: starburst galaxy first (first choices: Starburst Galaxy) (alternatives: Dremio)
- Kimi K2: starburst galaxy first (first choices: Starburst Galaxy) (alternatives: CData Connect Cloud, Dremio Cloud)
- Grok 4.1 Fast: neither first, one named (first choices: Denodo) (alternatives: Dremio, IBM Data Virtualization, Starburst Galaxy, TIBCO Data Virtualization)
- DeepSeek V4 Flash: neither first, one named (first choices: Denodo) (alternatives: Dremio, Starburst Galaxy, TIBCO Data Virtualization)
- MiniMax M2.5: neither first, one named (first choices: Denodo) (alternatives: TIBCO Data Virtualization, Teiid, Trino)
- Claude Haiku 4.5: neither named (first choices: Denodo) (alternatives: CData Virtuality, Dremio, TIBCO Data Virtualization)
- GPT-5.4 mini: neither named (first choices: Denodo) (alternatives: IBM Data Virtualization, TIBCO Data Virtualization)
- Gemini 3.5 Flash: neither named (first choices: CData Virtuality) (alternatives: CData Connect Cloud, Denodo, Dremio)
- Perplexity Sonar: neither named (first choices: Denodo) (alternatives: CData Virtuality, IBM Cloud Pak for Data, TIBCO Data Virtualization)
- Mistral Small: neither named (first choices: Informatica Data Virtualization, TIBCO Data Virtualization) (alternatives: CData Virtuality, IBM Data Virtualization, Red Hat JBoss Data Virtualization)
- Llama 4 Maverick: neither named
- GLM 4.7 FlashX: neither named (first choices: Denodo) (alternatives: IBM watsonx.data, Informatica Data Virtualization, TIBCO Data Virtualization)
- GPT-6 Luna: neither named (first choices: Denodo) (alternatives: Dremio, Starburst)
- Muse Glimmer 30B: neither named (first choices: AtScale, Dremio) (alternatives: Denodo, TIBCO Data Virtualization)

## What the models said about Trino

- "Trino/Starburst-style solutions can work well, but they may be the wrong choice if your use case needs heavy governance, complex business semantics" (GPT-5.4 mini, negative prompt, soft negative)
- "called out as open-source platforms with no certifications, which makes them risky in regulated environments" (Perplexity Sonar, negative prompt, soft negative)
- "Be cautious if you lack the team to own connectors, upgrades, security, and query tuning." (GPT-6 Luna, negative prompt, soft negative)
- "Start with Trino if you have technical resources - it's the most widely adopted open-source option" (Kimi K2, budget prompt, first choice)
- "Trino is the best data virtualization platform for a company with a limited budget" (MiniMax M2.5, budget prompt, first choice)
- "Trino if you have technical talent and want to avoid licensing costs entirely" (GLM 4.7 FlashX, budget prompt, first choice)

## What the models said about Starburst Galaxy

- "Choose Starburst Galaxy if you want the fastest setup, lowest administrative overhead, and variable costs that match your growth." (Qwen 3.7 Flash, direct prompt, first choice)
- "Starburst Galaxy stands out as one of the strongest options for a data virtualization platform" (Grok 4.1 Fast, budget prompt, first choice)
- "My default recommendation would be Starburst Galaxy for a mid-sized B2B company" (GPT-6 Luna, paraphrase prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.