DagsterData your team trusts. AI that runs on it.
vs
Ray ServeScalable model serving library for building online inference APIs
Comparison · MLOps Platforms · weekly run Nov 2
Dagster vs Ray Serve
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Dagster is the stronger AI pick in MLOps Platforms: it has a visibility score of 0.7 versus 0 for Ray Serve.
Choose Dagster if…
- You want the brand AI engines rank higher (0.7 vs 0)
- You need HIPAA coverage
- named as a practical orchestration choice
Choose Ray Serve if…
- You need ISO/IEC 27001 coverage
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Dagster | Ray Serve |
|---|---|---|
| Visibility score | 0.7% | 0% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #40 | #61 |
| Share of voice | 0.3% | 0% |
| Mentions this run | 2 | 0 |
| Positive in AI answers | 50% | — |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Dagster 0pp · Ray Serve 0pp over 0 weekly runs.
Engine by engine
Dagster leads on 1 of 3 engines
ChatGPT
AI Mode
Perplexity
DagsterRay Serve
Head to head in AI answers
0 engine answers name both brands
0Dagster ranked higher
0Ray Serve ranked higher
Features, pricing & fit
| Dimension | Dagster | Ray Serve |
|---|---|---|
| Pricing model | Usage-based | — |
| Entry price | $10 / mo | — |
| Free plan | No · 30-day trial | — |
| Deployment | Serverless or hybrid deployment; under hybrid, compute runs in the customer's own infrastructure while Dagster manages the control plane. | Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay |
| Compliance | SOC 2 Type II, HIPAA | SOC 2 Type II, ISO/IEC 27001 |
| Support | Dagster community, Support Center and Ask AI, Billing support, Dedicated Slack or Microsoft Teams channel (Pro plan) | Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray |
| Founded | 2018 | — |
| Headquarters | San Francisco, CA, United States | San Francisco, California |
| Employees | 51–200 | — |
| Funding | Series B · $49M raised | Series C |
| Best for | Data teams running dbt, Snowflake and Python data pipelines who want lineage and health visibility across their stack. | Python teams serving machine learning models, including LLMs, as online inference APIs that need independent scaling |
Plans side by side
Ray Serve
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
Dagster
- named as a practical orchestration choice
Ray Serve
Profile in progress.
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Dagster vs Ray Serve”, https://slateindex.ai/compare/dagster-vs-ray-serve, data of Nov 2, 2026. Licence: CC BY 4.0.