Apache DolphinScheduler vs Argo Workflows

Apache DolphinScheduler is a free, open-source workflow orchestration platform for designing and running data workflows through visual directed-acyclic-graph interfaces or code. Workflows can be built with drag-and-drop tools or defined in Python, YAML, or the Open API. The project lists more than 30 task types, including Shell, SQL, Spark, Flink, Hive, Kubernetes, and HTTP. Scheduling supports cross-project and cross-workflow dependencies, pause and resume operations, and serial or parallel batch backfills. A decentralized multi-master, multi-worker design is described as increasing scheduling capacity with cluster size. Deployment options are standalone, cluster, and Kubernetes. Standalone is for evaluation, recommended for fewer than 20 workflows, and its in-memory H2 database is cleared when the service stops or restarts. Authentication includes password, LDAP, Casdoor SSO, and OAuth2, with administrator-managed resource controls. The security model assumes a trusted network.

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.