Argo Workflows vs Orkes Conductor
Argo Workflows
argoproj.github.io
Orkes Conductor
orkes.ioSide by side
| Figure | Argo Workflows | Orkes Conductor |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · IT Orchestration Software | 8.7 (#3) | 7.5 (#18) |
| Deployment | Argo Workflows is cloud agnostic and can run on any Kubernetes cluster. | Orkes Cloud can be hosted by Orkes or in a customer cloud footprint, including Azure, AWS, GCP, or private cloud. |
| Integrations | The project lists Argo Events, Hera, Katib, Kedro, Kubeflow Pipelines, Netflix Metaflow, Piper, Seldon, and SQLFlow among projects that use or rely on Argo Workflows. | The pricing page identifies integrations spanning AI/LLM, message brokers, SDKs, relational databases, and vector databases. |
| Purpose | Argo Workflows is an open-source, container-native engine for orchestrating parallel jobs on Kubernetes. | Orkes Conductor brings AI agents and deterministic workflows together to build and scale business processes. |
| Support | The project directs users with questions to GitHub Discussions and Slack and describes monthly community meetings. | Enterprise support includes SLA-backed response times, multiple channels including email, support portal, Slack, and Teams, and a dedicated technical account manager. |
Plans
In their own words
Argo Workflows
Argo Workflows is a free, open-source engine for orchestrating container-based jobs on Kubernetes. Workflows can be arranged as sequential steps or as tasks linked in a directed acyclic graph, with each step running in a container. The project lists machine learning pipelines, data and batch processing, infrastructure automation, and CI/CD as use cases. Controls include loops, conditionals, retries, timeouts, suspension and resumption, cancellation, and limits on parallel work. Cron scheduling, workflow archiving, a UI for viewing and managing runs, and Prometheus metrics are included. Artifact support covers S3, Artifactory, Alibaba Cloud OSS, Azure Blob Storage, HTTP, Git, GCS, raw artifacts, and plugins. The server provides REST API support over HTTP and gRPC, with client libraries for Java, Go, Python, and TypeScript. Argo Workflows is self-hosted and can run on any Kubernetes cluster. Its listed plan costs nothing, and the official pages list no paid plans or usage limits. Administrators should configure transport security, authentication, roles, and permissions; workflow pods run as root by default unless their security context is set.
Orkes Conductor
Orkes Conductor combines AI agents with deterministic workflows for building and running business processes. Its durable execution preserves workflow and agent state through failures, restarts, outages and long-running interactions. Workflows can pause for approvals, reviews or escalations, then resume after a decision. Scheduling, webhooks and API triggers support event-driven automation. Monitoring includes real-time execution views, analytics, role-based access control, audit logs and input/output guardrails. Developers can use the Conductor SDK or bring LangGraph, OpenAI Agents SDK, Google ADK, CrewAI or custom agents. Orkes Cloud can be hosted by Orkes or deployed in a customer cloud footprint, including Azure, AWS, GCP or private cloud. Orkes says its cloud service is SOC 2 Type 2 compliant and encrypts data at rest and in transit. Cloud options include dedicated instances and private connectivity, and availability SLAs reach up to 99.99%. The free Developer Edition offers an individual sandbox and community support, but has no SLA and is not recommended for production. Enterprise pricing is custom and includes custom deployment options and Orkes Support.