Streaming platforms · November 2026 Edition
Apache Kafka vs Amazon MSK
One of fourteen models named Apache Kafka first on the direct prompt; zero named Amazon MSK. Both were named by all fourteen models and Apache Kafka carries 51 labels and Amazon MSK 37, so the shares are not directly comparable.
Named in three categories this edition.
Named in one category this edition.
First-choice share7%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate33%11%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 12; printed, not drawn.
Labels5137A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Apache Kafka reading right to left. Rank and label count are printed, not drawn.Confluent Cloud was named alongside these two in eleven of the fourteen direct answers. Confluent Cloud vs Apache Kafka · Confluent Cloud vs Amazon MSK · Redpanda vs Apache Kafka
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.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Apache KafkaFirst choices, of fourteen modelsAmazon MSK
Direct102 against Apache Kafka
Paraphrase01
Comparative110
Budget-constrained304 against Apache Kafka · 1 against Amazon MSK
Scale-constrained012 against Apache Kafka
Negative109 against Apache Kafka · 3 against Amazon MSK
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 November 2026 Edition, Apache Kafka and Amazon MSK were named in the same answer fifty-one times, of the 163 answers naming Apache Kafka and the 114 naming Amazon MSK. In those answers Amazon MSK took the first choice three times and Apache Kafka thirteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Apache Kafka and Amazon MSK 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 4.20 | | | | | | |
| 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 | | | | | |
Apache Kafka Amazon MSK first choice named as an alternative argued againstblank: not namedEach cell is one answer, Apache Kafka on the left and Amazon MSK on the right.The direct prompt
The plain question, one answer per model, grouped by where Apache Kafka and Amazon MSK stood in it.
Apache Kafka first, Amazon MSK not the choice
1 of 14 modelsAmazon MSK was named in the answer but not as the choice, or not at all.Claude Haiku 4.5Apache Kafka alternatives: Aiven for Apache Kafka, Amazon Kinesis Data Streams, Confluent Cloud
Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniConfluent Cloud alternatives: Apache Kafka, Redpanda
Grok 4.20Confluent Cloud alternatives: Amazon MSK, Azure Event Hubs, Google Cloud Pub/Sub, Redpanda
DeepSeek V4 FlashConfluent Cloud alternatives: Aiven for Apache Kafka, Amazon MSK, Redpanda
Qwen 3.7 FlashConfluent Cloud alternatives: Amazon Kinesis Data Streams, Amazon MSK, Azure Event Hubs, Google Cloud Pub/Sub
GLM 4.7 FlashXConfluent Cloud alternatives: Amazon MSK, Apache Pulsar, Google Cloud Pub/Sub
GPT-6 LunaConfluent Cloud alternatives: Amazon MSK, Redpanda
Neither was named
7 of 14 modelsThe answer made no first choice from these two in this category.Gemini 3.5 FlashConfluent Cloud alternatives: AWS EventBridge, Aiven for Apache Kafka, Amazon Kinesis Data Streams, Google Cloud Pub/Sub, Redpanda, Upstash Kafka
Perplexity SonarConfluent Cloud alternatives: Amazon Kinesis Data Streams, Azure Event Hubs, Bizzabo, Estuary, Redpanda
Mistral SmallAiven for Apache Kafka, Redpanda alternatives: Airmeet, Livestorm, Sequel
Llama 4 MaverickAirmeet alternatives: Goldcast, Livestorm
Kimi K2Demio alternatives: Confluent Cloud, Contrast, Goldcast, Livestorm, Redpanda
MiniMax M2.5Bizzabo alternatives: Livestorm, ON24
Muse Glimmer 30BConfluent Cloud alternatives: Redpanda
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
Apache Kafka leads by two points.
Apache Kafka2%#9 of 13Amazon MSK0%#10 of 13Mid-marketThe figures above
Apache Kafka leads by three points.
Apache Kafka7%#3 of 12Amazon MSK3%#6 of 12Enterprise
Apache Kafka leads by eight points.
Apache Kafka8%#2 of 9Amazon MSK0%#7 of 9What the models said about Apache Kafka
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Avoid Self-Hosting Kafka: The total cost of ownership (TCO) of engineer hours spent troubleshooting Kafka brokers... far exceeds the cost of a managed vendor.” Gemini 3.5 Flash · direct prompt · hard negative
“Why cautious/avoid: Extremely high operational complexity—requires deep expertise in clustering, KRaft mode, tuning, monitoring, scaling, and disaster recovery.” Grok 4.20 · negative prompt · soft negative
“Caution Due to Operational Complexity: Apache Kafka (and Confluent)... You shouldn't necessarily "avoid" it, but you must be extremely cautious.” Qwen 3.7 Flash · negative prompt · soft negative
“Apache Kafka (self-managed or open-source) is generally the best event streaming platform for a company with a limited budget.” Grok 4.20 · budget prompt · first choice
“The open-source standard for durable, replayable event streams... You want control, portability, and a widely used foundation” GPT-6 Luna · comparative prompt · first choice
“Apache Kafka (The Industry Standard) ... Choose Kafka if you need the most mature ecosystem, highest throughput ceiling” Kimi K2 · comparative prompt · first choice
What the models said about Amazon MSK
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Apache Kafka (including Confluent Cloud, MSK, Redpanda, etc.) ... Can become complex to operate at scale” GLM 4.7 FlashX · negative prompt · soft negative
“Amazon MSK has seen a decline in preference among some mid-market companies due to cost and complexity” Mistral Small · negative prompt · soft negative
“AWS MSK Serverless has a free tier for testing, but avoid full managed for cost” Grok 4.20 · budget prompt · soft negative
“Choose AWS MSK if 100% of your stack is on AWS and you want simple IAM security and consolidated cloud billing.” Gemini 3.5 Flash · paraphrase 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
“Great if you are heavily locked into AWS infra and want to keep vendor procurement simple, though developer tooling & UI are basic.” Gemini 3.5 Flash · scale prompt · alternative
Also compared
Confluent Cloud vs Apache KafkaConfluent Cloud vs Amazon MSKRedpanda vs Apache KafkaRedpanda vs Amazon MSKApache Kafka vs Google Cloud Pub/SubApache Kafka vs NATS JetStreamApache Kafka vs Aiven for Apache KafkaApache Kafka vs Amazon Kinesis Data StreamsGoogle Cloud Pub/Sub vs Amazon MSKNATS JetStream vs Amazon MSKAmazon MSK vs Aiven for Apache KafkaAmazon MSK vs Amazon Kinesis Data StreamsAll twenty-eight head-to-head pages and the full streaming 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.