One of fourteen models named Redpanda first on the direct prompt; zero named Amazon Kinesis Data Streams. Both were named by all fourteen models and Redpanda carries 54 labels and Amazon Kinesis Data Streams 43, 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 streaming platforms page.
Across every category in the November 2026 Edition, Redpanda and Amazon Kinesis Data Streams were named in the same answer eighty-four times, of the 153 answers naming Redpanda and the 119 naming Amazon Kinesis Data Streams. In those answers Amazon Kinesis Data Streams took the first choice three times and Redpanda fifteen.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| 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 |
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.
“Review the license carefully if you plan to build a service on top of it or depend on enterprise features.” GPT-6 Luna · negative prompt · soft negative
“Apache Kafka (including Confluent Cloud, MSK, Redpanda, etc.) ... Can become complex to operate at scale” GLM 4.7 FlashX · negative prompt · soft negative
“check its documented compatibility limits against your specific Kafka features and clients” GPT-6 Luna · comparative prompt · soft negative
“Redpanda Cloud: Kafka-compatible, C++ architecture (no Java JVM tuning), ultra-fast performance, simple operations, cost-effective for high throughput.” Gemini 3.5 Flash · scale prompt · first choice
“Needs Kafka API + Lowest Infra Cost | Redpanda (Community) | Saves up to 60–80% on compute vs Kafka; no JVM.” Gemini 3.5 Flash · budget prompt · first choice
“Aiven or Redpanda – These are often cited as the best choices for small to mid-market companies” Mistral Small · direct prompt · first choice
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 or rethink Kinesis (legacy API) and Pub/Sub if you need long‑term replay or durable event logs.” GLM 4.7 FlashX · negative prompt · hard negative
“Avoid managed cloud services (AWS Kinesis, Azure Event Hubs, Confluent Cloud) if budget is tight” Kimi K2 · budget prompt · hard negative
“internal tech-radar assessments note deprecation” Muse Glimmer 30B · negative prompt · hard negative
“All-in on one hyperscaler with a lean platform team → Native cloud service Kinesis, Event Hubs, Pub/Sub.” Muse Glimmer 30B · scale prompt · first choice
“Start with managed Kafka (Confluent Cloud or MSK) for 6-12 months to validate use cases” GLM 4.7 FlashX · scale prompt · first choice
“AWS-native workloads | Amazon Kinesis | Natural fit when applications, security, and operations already center on AWS.” Perplexity Sonar · direct prompt · alternative
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.