Data virtualization · October 2026 Edition
Starburst vs TIBCO Data Virtualization
Zero of fourteen models named Starburst first on the direct prompt; one named TIBCO Data Virtualization. Starburst was named by thirteen of the fourteen models and TIBCO Data Virtualization by twelve and Starburst carries 32 labels and TIBCO Data Virtualization 34, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
First-choice share11%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%35%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 10; printed, not drawn.
Labels3234A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Starburst reading right to left. Rank and label count are printed, not drawn.Denodo was named alongside these two in ten of the fourteen direct answers. Denodo vs Starburst · Denodo vs TIBCO Data Virtualization · Trino vs Starburst
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 data virtualization page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
StarburstFirst choices, of fourteen modelsTIBCO Data Virtualization
Direct01
Paraphrase50
Comparative011 against TIBCO Data Virtualization
Budget-constrained001 against Starburst · 3 against TIBCO Data Virtualization
Scale-constrained101 against Starburst · 1 against TIBCO Data Virtualization
Negative107 against TIBCO Data Virtualization
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.
Across every category in the October 2026 Edition, Starburst and TIBCO Data Virtualization were named in the same answer thirty-six times, of the 82 answers naming Starburst and the 96 naming TIBCO Data Virtualization. In those answers TIBCO Data Virtualization took the first choice one time and Starburst three.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Starburst and TIBCO Data Virtualization 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 | | | | |
Starburst TIBCO Data Virtualization first choice named as an alternative argued againstblank: not namedEach cell is one answer, Starburst on the left and TIBCO Data Virtualization on the right.The direct prompt
The plain question, one answer per model, grouped by where Starburst and TIBCO Data Virtualization stood in it.
TIBCO Data Virtualization first, Starburst not the choice
1 of 14 modelsStarburst was named in the answer but not as the choice, or not at all.Mistral SmallInformatica Data Virtualization, TIBCO Data Virtualization alternatives: CData Virtuality, IBM Data Virtualization, Red Hat JBoss Data Virtualization
Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5Denodo alternatives: CData Virtuality, Dremio, TIBCO Data Virtualization
GPT-5.4 miniDenodo alternatives: IBM Data Virtualization, TIBCO Data Virtualization
Perplexity SonarDenodo alternatives: CData Virtuality, IBM Cloud Pak for Data, TIBCO Data Virtualization
Grok 4.1 FastDenodo alternatives: Dremio, IBM Data Virtualization, Starburst Galaxy, TIBCO Data Virtualization
DeepSeek V4 FlashDenodo alternatives: Dremio, Starburst Galaxy, TIBCO Data Virtualization
GLM 4.7 FlashXDenodo alternatives: IBM watsonx.data, Informatica Data Virtualization, TIBCO Data Virtualization
MiniMax M2.5Denodo alternatives: TIBCO Data Virtualization, Teiid, Trino
GPT-6 LunaDenodo alternatives: Dremio, Starburst
Muse Glimmer 30BAtScale, Dremio alternatives: Denodo, TIBCO Data Virtualization
Neither was named
4 of 14 modelsThe answer made no first choice from these two in this category.Gemini 3.5 FlashCData Virtuality alternatives: CData Connect Cloud, Denodo, Dremio
Llama 4 Maverickno first choice
Qwen 3.7 FlashStarburst Galaxy alternatives: Dremio
Kimi K2Starburst Galaxy alternatives: CData Connect Cloud, Dremio Cloud
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
Starburst leads by four points.
Starburst4%#8 of 12TIBCO Data Virtualization0%#12 of 12Mid-marketThe figures above
Starburst leads by nine points.
Starburst11%#4 of 10TIBCO Data Virtualization2%#7 of 10Enterprise
The order flips: TIBCO Data Virtualization leads at enterprise.
TIBCO Data Virtualization5%#2 of 8Starburst0%#6 of 8What the models said about Starburst
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Starburst | Contact sales (commercial) | While Trino-based, paid plans get expensive” DeepSeek V4 Flash · budget prompt · hard negative
“Starburst | Modern, Trino-based, cloud-native | Newer, smaller ecosystem” Kimi K2 · scale prompt · soft negative
“Leaders like Denodo ... Starburst consistently rank high for enterprise use, with strong governance and hybrid support.” Grok 4.1 Fast · negative prompt · first choice
“Start with Starburst Enterprise or Dremio Cloud... Starburst is the more "pure" federated query engine” Muse Glimmer 30B · paraphrase prompt · first choice
“I recommend Starburst (using the open-source Trino engine) as the primary choice” Qwen 3.7 Flash · paraphrase prompt · first choice
What the models said about TIBCO Data Virtualization
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“one data science professional described their experience with a TIBCO-based platform as "so slow and shitty"” DeepSeek V4 Flash · negative prompt · hard negative
“Highly proprietary enterprise suites like Denodo and TIBCO Data Virtualization ... tend to come with premium pricing, operational complexity, and a risk of lock-in” GPT-5.4 mini · negative prompt · soft negative
“Older versions of platforms from Tibco, Cisco Data Virtualization, and legacy IBM offerings that haven't been updated for modern cloud workloads.” Kimi K2 · negative prompt · soft negative
“Choose Starburst if you are building a modern data stack centered around cloud object storage (S3/ADLS) and need fast SQL queries over massive datasets.” Qwen 3.7 Flash · comparative prompt · first choice
“Informatica and TIBCO are top choices due to their scalability and integration capabilities” Mistral Small · direct prompt · first choice
“Consider IBM Cloud Pak for Data or TIBCO Data Virtualization if your existing stack already leans toward those ecosystems” Perplexity Sonar · direct prompt · alternative
Also compared
Denodo vs StarburstDenodo vs TIBCO Data VirtualizationTrino vs StarburstTrino vs TIBCO Data VirtualizationStarburst Galaxy vs StarburstStarburst Galaxy vs TIBCO Data VirtualizationStarburst vs DremioStarburst vs CData VirtualityDremio vs TIBCO Data VirtualizationCData Virtuality vs TIBCO Data VirtualizationAll twenty-one head-to-head pages and the full data virtualization 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.