Vendor Name | Metaflow |
Stand-alone vs. Platform | Standalone platform |
Delivery Model | Open-source or managed |
Clouds Supported | Cloud-native, available in your VPC on public cloud and/or Kubernetes. |
Pricing Model | Open-source |
Service Level Guarantees | For enterprise plans |
Support | Community support on Slack, with additional channels and SLA for enterprise plans. |
SSO, ACL | SSO for enterprise plans. |
Security and Compliance | Depends on deployment type, typically implemented by the customer as data stays in the customer cloud account. |
Setup | For greenfield environment, we provide cookie-cutter deployment templates that can be deployed in ~1 click. For customers that need tighter integration with existing infra, it depends but there aren't too many moving pieces in Metaflow itself. |
Flexibility, Speed, and Accessibility | Smooth integration with other tools is a core part of the value prop. |
Model Versioning, Lineage, and Packaging | Provides holistic versioning and reproducibility of your ML pipeline artifacts (not just models) and environments with dependencies. |
Log and Display of Metadata | You can log and see logs in real-time; for experiment metadata, you can store it as Metaflow artifacts. You have a full record of runs, but Metaflow is not opinionated about the format or specific metrics and can be used with specialized experiment metadata tracking libraries. |
Comparing Experiments and Models | Provides holistic versioning and reproducibility of your ML pipeline artifacts (not just models) and execution environments with dependencies. Visualization is up to you (or your favorite modality-specific library). |
Organizing and Searching Experiments and Models | There is a hierarchy of flows/runs/steps with a full audit trail and reproducibility. |
Model Review, Collaboration, and Sharing | You can implement your audit and review processes by using Metaflow tagging capabilities. |
CI/CD/CT Compatibility | Integration with Argo on K8S and Step Functions on AWS for production. |
Integrations | The integration philosophy is very open so with most tools Metaflow doesn't get in the way; so far the focus has been on integrating with cloud-native modern data stack and notebooks. |
There are no reviews yet. Be the first to write one.
Vendor |
Demo link |
Stand-alone vs. Platform |
Delivery Model |
Clouds Supported |
Pricing Model |
Service Level Guarantees |
Support |
SSO, ACL |
Security and Compliance |
Setup |
Flexibility, Speed, and Accessibility |
Model Versioning, Lineage, and Packaging |
Log and Display of Metadata |
Comparing Experiments and Models |
Organizing and Searching Experiments and Models |
Model Review, Collaboration, and Sharing |
CI/CD/CT Compatibility |
Integrations |