Domino Data LabThe enterprise AI platform to build, scale, and govern AI-powered applications
vs
KubeflowThe Open Source AI Platform
Comparison · MLOps Platforms · weekly run Nov 2
Domino Data Lab vs Kubeflow
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Kubeflow is the stronger AI pick in MLOps Platforms: it has a visibility score of 20.1 versus 5.6 for Domino Data Lab, and ranks ahead in 45% of the answers that name both.
Choose Domino Data Lab if…
- AI answers describe it more positively (35% vs 17% positive)
- You need ISO 27001 or ISO 9001 or SOC 2 or HIPAA or GDPR coverage
- You prefer a larger, established vendor (201–500 employees)
- Reproducible development environments
Choose Kubeflow if…
- You want the brand AI engines rank higher (20.1 vs 5.6)
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Domino Data Lab | Kubeflow |
|---|---|---|
| Visibility score | 5.6% | 20.1% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #15 | #9 |
| Share of voice | 2.5% | 5.8% |
| Mentions this run | 17 | 39 |
| Positive in AI answers | 35% | 17% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Domino Data Lab 0pp · Kubeflow 0pp over 0 weekly runs.
Engine by engine
Kubeflow leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
Domino Data LabKubeflow
Head to head in AI answers
11 engine answers name both brands
6Domino Data Lab ranked higher
5Kubeflow ranked higher
| Prompt | Engine | Domino Data Lab | Kubeflow |
|---|---|---|---|
| What are the best MLOps Platforms tools in 2026? | ChatGPT | #11 | #6 |
| What are the best MLOps Platforms tools in 2026? | Perplexity | #11 | #9 |
| Best MLOps platform for enterprise | Perplexity | #7 | #9 |
| Compare the leading MLOps Platforms platforms | ChatGPT | #10 | #6 |
| Compare the leading MLOps Platforms platforms | Perplexity | #10 | #7 |
| Best MLOps platform with AI features | ChatGPT | #10 | #9 |
| Which MLOps Platforms vendors do analysts recommend? | Perplexity | #9 | #11 |
| What is the typical pricing model for MLOps Platforms software? | ChatGPT | #7 | #10 |
| Official website of the top MLOps platform vendors | ChatGPT | #8 | #14 |
| Official website of the top MLOps platform vendors | AI Mode | #6 | #13 |
| Official website of the top MLOps platform vendors | Perplexity | #9 | #14 |
Features, pricing & fit
| Dimension | Domino Data Lab | Kubeflow |
|---|---|---|
| Pricing model | Flat tiers | — |
| Entry price | Contact sales | — |
| Free plan | No | — |
| Deployment | Single-tenant managed SaaS (Domino Cloud), or self-managed in the customer's VPC or on-premises, with hybrid and multicloud operation via Domino Nexus. Runs on Kubernetes. | Runs as a collection of microservices on any Kubernetes cluster, including on-premises, hybrid, and AWS, Azure, or GCP. |
| Compliance | ISO 27001, ISO 9001, SOC 2, HIPAA, GDPR | — |
| Support | Premium support with 2 business day response for non-urgent issues and 2 hour response for urgent issues, Enterprise support with 1 business day response for non-urgent issues and 1 hour response for urgent issues, Designated customer success manager on Enterprise plans, Security team available 24/7 for enterprise customers | Weekly community calls, Mailing list, Slack workspace |
| Founded | 2013 | 2017 |
| Headquarters | San Francisco, CA | Sunnyvale, CA, United States |
| Employees | 201–500 | 51–200 |
| Funding | Strategic equity investment from UBS · $228M raised | — |
| Best for | Large enterprises in regulated industries such as life sciences, financial services and the public sector, especially code-first data science teams. | — |
Plans side by side
Domino Data Lab
Domino CloudCustomsubscription
PremiumCustomsubscription
EnterpriseCustomsubscription
Kubeflow
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
Domino Data Lab
- Reproducible development environments
- Centralized governance and lifecycle policy enforcement
- Suited to collaborative, governed enterprise data science at scale
- Analyst recognition, such as a Gartner Visionary placement
Kubeflow
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
- modular, open-source infrastructure
- operationally complex, especially for small teams
- requires Kubernetes expertise and significant infrastructure ownership
- Kubernetes operations add infrastructure costs
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Domino Data Lab vs Kubeflow”, https://slateindex.ai/compare/domino-data-lab-vs-kubeflow, data of Nov 2, 2026. Licence: CC BY 4.0.