Domino Data Lab vs Polyaxon
Domino Data Lab
domino.ai
Polyaxon
polyaxon.comSide by side
| Figure | Domino Data Lab | Polyaxon |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 1 |
| Spec score · Experiment Tracking | 7.4 (#9) | 7.3 (#13) |
| Spec score · MLOps Platforms | 7.5 (#12) | 7.2 (#16) |
| Deployment | Domino supports deployment of apps such as Streamlit, Dash, and Shiny, which can scale with user demand and use discovery and approval workflows. | Polyaxon offers a managed cloud service and self-hosted deployments, including Community and Enterprise editions. |
| Purpose | Domino’s Enterprise AI Platform brings together model development, MLOps, collaboration, and governance for enterprises building and operating AI at scale. | Polyaxon is an AI engineering control plane for running machine learning, training, inference, and agent workloads on Kubernetes. |
| Support | All plans include premium or enterprise support; the pricing page lists a two-business-day support SLA for Cloud and Premium and a one-business-day SLA for Enterprise. | For self-hosting issues, the setup guide directs users to troubleshooting, GitHub Discussions, or GitHub bug reports and feature requests. |
Plans
Domino Data Lab
- Domino CloudPriced on request
- EnterprisePriced on request
- PremiumPriced on request
In their own words
Domino Data Lab
Domino Data Lab has no write-up on Specifiction yet; its figures are above.
Polyaxon
Polyaxon is an AI engineering control plane for machine-learning training, inference and agent workloads on Kubernetes. It records run parameters, metrics, logs, code versions, artifacts, lineage and runtime state. Orchestration covers jobs, services, DAGs, schedules, sweeps, distributed workloads and reusable components. Isolated execution environments can be launched with controlled filesystems, network access, tools, SSH and runtime policies. Evaluation and monitoring include offline and online evaluations, logs, traces, metrics, health checks, alerts and dashboards. Listed integrations include PyTorch, TensorFlow, Hugging Face, LangChain, Ray, Dask, Spark, AWS, GCP, Azure, GitHub, GitLab, Slack and Datadog. Deployment is available through managed cloud or self-hosted Community and Enterprise editions. The core is Apache 2.0 licensed. A free Community Edition covers one cluster and namespace; paid access starts at $555/mo.