Choosing a Workflow Orchestration Framework
Several considerations influence the selection of the most suitable tool:
- Nature of your tasks: Are you orchestrating existing standalone executables or scripts (e.g., bioinformatics tools that need to run in a specific order), or are you building workflows around code you’re actively developing (e.g., in Python or R)?
- Target platform: What is your primary execution environment? Options include local computers, cloud services, HPC clusters, or a combination of these.
- Community and support: How active is the tool’s community? Is there good documentation, active maintenance, and community resources?
- Learning curve: How much time and effort are you willing to invest in learning the tool? Some tools have steeper learning curves but offer more features.
- Feature completeness: Does the tool provide the features you need (e.g., scheduling, monitoring, error handling, container support, distributed execution)?
There is no single solution that fits all use cases. The table below can help guide your decision.
This is not an exhaustive list—many additional workflow orchestration tools exist. Pull requests to add other tools are welcome!
| Orchestrator | Scope | Language Support | Adoption | Learning Curve | Location | Best-Fit Use Cases | Deployment Model |
|---|---|---|---|---|---|---|---|
| Airflow | Generalist ETL | Python | Very broad | Moderate–Steep | Cloud / On-prem / Hybrid | Enterprise ETL/ELT, scheduled business workflows | Self-host, Kubernetes, or managed services (MWAA, Composer) |
| Argo Workflows | Kubernetes-native | Containers | Growing | Moderate–Steep | Cloud / Hybrid | Containerized CI/CD, data and ML pipelines on K8s | Kubernetes-native YAML workflows |
| Luigi | Generalist | Python | Moderate | Moderate | Local / On-prem | Dependency-based pipelines, smaller ETL workloads | Local or on-prem VM deployments |
| Nextflow | Scientific / HPC | Any executables; Groovy DSL | Broad (science) | Moderate | HPC / Cloud / Hybrid | Reproducible scientific workflows, genomics, containerized HPC jobs | Local, Slurm/PBS/LSF, AWS Batch, Google Life Sciences |
| Snakemake | Scientific / HPC | Python DSL | Broad (academia) | Easy–Moderate | Local / HPC / Hybrid | Lab-scale pipelines, reproducible research workflows | Local, Slurm/PBS, Kubernetes via profiles |
| Common Workflow Language (CWL) | Scientific | standard YAML/JSON spec for any executables | Broad (standards-driven) | Moderate–Steep | Local / Cloud / HPC | Portable, standards-based scientific workflows | Executed via engines (cwltool, Toil, Cromwell, Arvados) |
| Prefect | Generalist | Python + any executables | Broad / growing | Easy–Moderate | Local / Cloud / Hybrid | General automation, light ETL, ML pipelines, coordinating Dask/Ray/Spark | Prefect Cloud or self-host; tasks run anywhere |
| Dagster | Data engineering | Python | Broad / growing | Moderate | Local / Cloud / Hybrid | Asset-based pipelines, lineage-heavy analytics, ML feature pipelines | Dagster Cloud or self-host; local/K8s executors |
| Cromwell / WDL | Genomics | WDL DSL | Broad in genomics | Moderate | HPC / Cloud / Hybrid | GATK and large genomics pipelines | Local, Slurm/PBS, AWS Batch, Google Life Sciences |
| targets (R) | Generalist (R-centric) | R-first; supports external files & commands | High in R community | Moderate | Local / HPC / Hybrid | Reproducible R analysis pipelines, research workflows, ML experiments | Local execution; integrates with HPC via future/batchtools |
Footnotes:
- ETL = Extract, Transform, Load
- ELT = Extract, Load, Transform
- CI/CD = Continuous Integration / Continuous Deployment
- ML = Machine Learning
- K8s = Kubernetes
- DSL = Domain-Specific Language
- HPC = High-Performance Computing
- PBS = Portable Batch System
- LSF = Load Sharing Facility
- WDL = Workflow Description Language
- GATK = Genome Analysis Toolkit
- AWS = Amazon Web Services
- Slurm = Simple Linux Utility for Resource Management (Slurm Workload Manager)
- VM = Virtual Machine
- MWAA = Managed Workflows for Apache Airflow
- YAML = YAML Ain’t Markup Language