DagsHubEverything you need to manage multimodal AI data & models.
vs
Domino Data LabThe enterprise AI platform to build, scale, and govern AI-powered applications
Comparison · MLOps Platforms · weekly run Nov 2
DagsHub vs Domino Data Lab
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Domino Data Lab is the stronger AI pick in MLOps Platforms: it has a visibility score of 5.6 versus 3.5 for DagsHub.
Choose DagsHub if…
- You want a free plan to start
- Per seat pricing suits your budget better than flat tiers
- Structured annual pricing with yearly billing options on team tiers
- Recommended as a starting option for MLOps lifecycle coverage
Choose Domino Data Lab if…
- You want the brand AI engines rank higher (5.6 vs 3.5)
- You need a self-hosted or on-premises option
- You need ISO 27001 or ISO 9001 or SOC 2 or HIPAA or GDPR coverage
- You prefer a larger, established vendor (201–500 employees)
AI visibility side by side
Latest weekly run · Nov 2
| Metric | DagsHub | Domino Data Lab |
|---|---|---|
| Visibility score | 3.5% | 5.6% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #23 | #15 |
| Share of voice | 0.6% | 2.5% |
| Mentions this run | 4 | 17 |
| Positive in AI answers | — | 35% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
DagsHub 0pp · Domino Data Lab 0pp over 0 weekly runs.
Engine by engine
Domino Data Lab leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
DagsHubDomino Data Lab
Head to head in AI answers
0 engine answers name both brands
0DagsHub ranked higher
0Domino Data Lab ranked higher
Features, pricing & fit
| Dimension | DagsHub | Domino Data Lab |
|---|---|---|
| Pricing model | Per seat | Flat tiers |
| Entry price | Free; paid from $119 per seat / mo | Contact sales |
| Free plan | Yes | No |
| Deployment | Cloud hosting, with on-premise, VPC, and air-gapped installation on the Enterprise plan. | 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. |
| Compliance | — | ISO 27001, ISO 9001, SOC 2, HIPAA, GDPR |
| Support | Community chat and email, Priority support on the Team plan, Enterprise SLA and 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 |
| Founded | 2019 | 2013 |
| Headquarters | San Francisco, California, United States | San Francisco, CA |
| Employees | 11–50 | 201–500 |
| Funding | Accelerator/incubator deal | Strategic equity investment from UBS · $228M raised |
| Best for | Data science and AI teams that manage multimodal datasets, experiments, and models, from individuals building small applications to enterprises running high-scale workloads. | 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
DagsHub
Individual$0user/month
Team$119user/month (monthly); $99 billed yearly
EnterpriseCustomcustom quote
Domino Data Lab
Domino CloudCustomsubscription
PremiumCustomsubscription
EnterpriseCustomsubscription
Pros and cons
Themes from the AI answers that mention each brand
DagsHub
- Structured annual pricing with yearly billing options on team tiers
- Recommended as a starting option for MLOps lifecycle coverage
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
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “DagsHub vs Domino Data Lab”, https://slateindex.ai/compare/dagshub-vs-domino-data-lab, data of Nov 2, 2026. Licence: CC BY 4.0.