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Index › Cloud and infrastructure › Managed Kubernetes › Amazon EKS vs DigitalOcean Kubernetes
Managed Kubernetes platforms · October 2026 Edition

Amazon EKS vs DigitalOcean Kubernetes

Three of fourteen models named Amazon EKS first on the direct prompt; zero named DigitalOcean Kubernetes. Amazon EKS was named by fourteen of the fourteen models and DigitalOcean Kubernetes by thirteen and Amazon EKS carries 71 labels and DigitalOcean Kubernetes 47, so the shares are not directly comparable.

Amazon EKS

criticized challenger

Named in one category this edition.

DigitalOcean Kubernetes

accepted challenger

Named in one category this edition.

First-choice share15%14%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate32%21%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 10; printed, not drawn.
Labels7147A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Amazon EKS reading right to left. Rank and label count are printed, not drawn.Google Kubernetes Engine was named alongside these two in twelve of the fourteen direct answers. Google Kubernetes Engine vs Amazon EKS · Google Kubernetes Engine vs DigitalOcean Kubernetes · Amazon EKS vs Azure Kubernetes Service

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 managed kubernetes 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.
Amazon EKSFirst choices, of fourteen modelsDigitalOcean Kubernetes
Direct302 against Amazon EKS
Paraphrase50
Comparative20
Budget-constrained099 against Amazon EKS
Scale-constrained20
Negative0012 against Amazon EKS · 10 against DigitalOcean Kubernetes
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, Amazon EKS and DigitalOcean Kubernetes were named in the same answer 107 times, of the 214 answers naming Amazon EKS and the 121 naming DigitalOcean Kubernetes. In those answers DigitalOcean Kubernetes took the first choice forty-four times and Amazon EKS seven.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Amazon EKS and DigitalOcean Kubernetes stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Amazon EKS DigitalOcean Kubernetes first choice named as an alternative argued againstblank: not namedEach cell is one answer, Amazon EKS on the left and DigitalOcean Kubernetes on the right.

The direct prompt

The plain question, one answer per model, grouped by where Amazon EKS and DigitalOcean Kubernetes stood in it.

Amazon EKS first, DigitalOcean Kubernetes an alternative

3 of 14 modelsDigitalOcean Kubernetes was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Amazon EKS, Google Kubernetes Engine alternatives: DigitalOcean Kubernetes, Linode Kubernetes Engine
GPT-5.4 miniAmazon EKS, Google Kubernetes Engine
Mistral SmallAmazon EKS, Azure Kubernetes Service, Google Kubernetes Engine alternatives: DigitalOcean Kubernetes, Rancher, Red Hat OpenShift

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DigitalOcean Kubernetes
Grok 4.1 FastGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DOKS, RKE2, Rancher
DeepSeek V4 FlashGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DigitalOcean Kubernetes
Qwen 3.7 FlashMicrosoft Azure alternatives: Amazon EKS, DigitalOcean Kubernetes, Google Cloud, Linode Kubernetes Engine, Rancher
Kimi K2Azure Kubernetes Service alternatives: DigitalOcean Kubernetes, Google Kubernetes Engine
GLM 4.7 FlashXGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, Oracle Container Engine for Kubernetes, Rackspace Spot
Muse Glimmer 30BGoogle Kubernetes Engine alternatives: Amazon EKS, Azure Kubernetes Service, DigitalOcean Kubernetes

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarGoogle Kubernetes Engine alternatives: Azure Kubernetes Service, Northflank, Red Hat OpenShift
Llama 4 MaverickLinode Kubernetes Engine alternatives: Northflank, Platform9 Managed Kubernetes
MiniMax M2.5Azure Kubernetes Service, Google Kubernetes Engine alternatives: Platform9 Managed Kubernetes, Rancher
GPT-6 LunaGoogle Kubernetes Engine alternatives: AKS Automatic, Amazon EKS Auto Mode

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
DigitalOcean Kubernetes leads by fifty-three points.
DigitalOcean Kubernetes55%#1 of 10
Amazon EKS2%#7 of 10
The full small business standing →
Mid-marketThe figures above
The order flips: Amazon EKS leads at mid-market.
Amazon EKS15%#2 of 10
DigitalOcean Kubernetes14%#3 of 10
The full mid-market standing →
Enterprise
Amazon EKS leads by twenty-five points.
Amazon EKS25%#2 of 9
DigitalOcean Kubernetes0%#9 of 9
The full enterprise standing →

What the models said about Amazon EKS

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 EKS / AKS / GKE if you need low operational overhead on a tight budget or want maximum portability.” Muse Glimmer 30B · negative prompt · hard negative
“Avoid for tight budgets: Big 3 (GKE/AKS/EKS) due to control plane fees” Grok 4.1 Fast · budget prompt · hard negative
“"the worst managed Kubernetes provider out of all the major players."” MiniMax M2.5 · negative prompt · hard negative
“AWS EKS or Google GKE are often the safest bets due to their maturity, extensive ecosystems, and reliability” Claude Haiku 4.5 · direct prompt · first choice
“For most teams, the shortlist is Amazon EKS, Google Kubernetes Engine (GKE), and Azure Kubernetes Service (AKS).” GPT-6 Luna · comparative prompt · first choice
“Go with Amazon EKS (with Karpenter) if you are already on AWS and want the largest ecosystem of tools and talent.” Gemini 3.5 Flash · paraphrase prompt · first choice

What the models said about DigitalOcean Kubernetes

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 Avoid or Use with Caution ### 1. DigitalOcean Kubernetes - Main concerns: No enterprise-grade SLA” GLM 4.7 FlashX · negative prompt · hard negative
“Avoid smaller providers if you need robust, scalable, and fully supported production environments.” Mistral Small · negative prompt · hard negative
“Status: ❌ Generally Avoid for Enterprise/Critical Workloads” Qwen 3.7 Flash · negative prompt · hard negative
“I'd recommend starting with DigitalOcean or Civo as they offer the best balance of cost, simplicity, and reliability” MiniMax M2.5 · budget prompt · first choice
“DigitalOcean's DOKS (DigitalOcean Kubernetes) stands out as one of the best-managed options among reliable providers.” Grok 4.1 Fast · budget prompt · first choice
“the strongest default choice is usually DigitalOcean Kubernetes because it has a free control plane” Perplexity Sonar · budget prompt · first choice
Also compared

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.