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

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

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Denodo | 28% | #1 of 10 | 35% | 66 | 14 of 14 |
| Starburst Galaxy | 13% | #3 of 10 | 0% | 13 | 9 of 14 |

## The direct prompt, model by model

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

## What the models said about Denodo

- "What to Avoid on a Tight Budget ... Denodo | ~$180,000/year | Enterprise pricing is out of reach" (DeepSeek V4 Flash, budget prompt, hard negative)
- "Premium enterprise - avoid for limited budgets" (Kimi K2, budget prompt, hard negative)
- "Highly proprietary enterprise suites like Denodo and TIBCO Data Virtualization can be strong technically, but they tend to come with premium pricing, operational complexity, and a risk of lock-in" (GPT-5.4 mini, negative prompt, soft negative)
- "the strongest default choice is usually Denodo if you need broad connectivity, governance, and a mature enterprise-grade virtualization layer" (Perplexity Sonar, direct prompt, first choice)
- "Choose Denodo if you need the most comprehensive, enterprise-grade data virtualization with the broadest source connectivity and governance." (DeepSeek V4 Flash, comparative prompt, first choice)
- "Denodo is a pure-play logical data fabric, while TIBCO emphasizes a semantic layer and SQL-based cross-source joins with pushdown." (Muse Glimmer 30B, comparative 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.