Zero of fourteen models named Reltio Connected Data Platform first on the direct prompt; zero named Informatica MDM. Both were named by all fourteen models and Reltio Connected Data Platform carries 49 labels and Informatica MDM 57, so the shares are not directly comparable.
Named in one category this edition.
Named in two categories this edition.
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 master data management page.
Across every category in the November 2026 Edition, Reltio Connected Data Platform and Informatica MDM were named in the same answer 117 times, of the 130 answers naming Reltio Connected Data Platform and the 177 naming Informatica MDM. In those answers Informatica MDM took the first choice thirty-one times and Reltio Connected Data Platform six.
| Model | DirectRC | ParaphraseRC | ComparativeRC | Budget-constrainedRC | Scale-constrainedRC | NegativeRC |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | RC | |||||
| GPT-5.4 mini | RC | RC | ||||
| Gemini 3.5 Flash | RC | RC | RC | RC | ||
| Perplexity Sonar | RC | RC | ||||
| Grok 4.20 | RC | RC | RC | |||
| Mistral Small | RC | RC | ||||
| DeepSeek V4 Flash | RC | RC | RC | RC | RC | |
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | RC | RC | RC | |||
| Kimi K2 | RC | RC | RC | RC | ||
| GLM 4.7 FlashX | RC | RC | ||||
| MiniMax M2.5 | RC | RC | ||||
| GPT-6 Luna | RC | RC | RC | RC | ||
| Muse Glimmer 30B | RC | RC | RC |
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.
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 beginning with Informatica, Reltio, or similar enterprise platforms” Perplexity Sonar · budget prompt · hard negative
“Avoid: Enterprise platforms like ... Reltio” DeepSeek V4 Flash · budget prompt · hard negative
“Treat this as a strategic and roadmap risk to investigate, not evidence that Reltio's technology is deficient.” GPT-6 Luna · negative prompt · soft negative
“Reltio is widely cited as the best option for organizations moving away from heavy, legacy infrastructure toward a modern, real-time cloud solution.” Qwen 3.7 Flash · paraphrase prompt · first choice
“Reltio is frequently cited for its use-case-driven, graph-based approach that excels at customer and product data unification.” Qwen 3.7 Flash · comparative prompt · alternative
“Reltio is a cloud-native platform built around customer data and entity resolution across large record volumes.” Claude Haiku 4.5 · direct prompt · alternative
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Platforms to Watch Out For (Contextual): Solutions like Informatica MDM (pre-cloud acquisitions)... Do not buy these if you need a "plug and play" solution” Qwen 3.7 Flash · negative prompt · hard negative
“Avoid for budgets: Enterprise-heavy tools like IBM InfoSphere, Informatica, SAS Viya, or Oracle MDM” Grok 4.20 · budget prompt · hard negative
“Avoid for most mid-sized B2B: Informatica or SAP MDG (too heavy/expensive/slow to deploy” Grok 4.20 · paraphrase prompt · hard negative
“Long recognized as a leader in enterprise data management, Informatica offers a multidomain MDM solution fully integrated into its broader IDMC platform.” Gemini 3.5 Flash · comparative prompt · first choice
“Strong for enterprise-grade functionality with good scalability, customer/product data management, and integration capabilities.” Claude Haiku 4.5 · paraphrase prompt · first choice
“Large, complex enterprises with diverse stacks: Informatica MDM or IBM MDM (for hybrid/cloud and security).” GLM 4.7 FlashX · comparative prompt · first choice
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.