Stof vs. Temporal/Airflow

TL;DR

• Temporal, Airflow, and Prefect are workflow orchestration platforms with servers, databases, UIs, and heavy infrastructure

• Stof is a lightweight document format where workflows are portable, executable data

Key difference: Temporal/Airflow require infrastructure to run. Stof workflows are just documents you can execute anywhere.

Comparison

All let you:

• Define multi-step workflows

• Handle retries and error recovery

• Orchestrate distributed tasks

• Track workflow state and history

Feature	Temporal	Airflow	Perfect	Stof
Architecture	Server + Workers	Server + Scheduler + Workers	Server + Agents	No server needed
Infrastructure	Required	Required	Required	Optional
Format	Code (Go, Python, Java)	Python DAGs	Python flows	Stof documents
Deployment	Complex	Complex	Medium	Copy a file
Portability	Tied to Cluster	Tied to Instance	Tied to Cloud Server	Run anywhere
Size overhead	~100MB + runtime	~500MB + deps	~50MB + runtime	~4MB runtime
State management	Database required	Database required	Database required	Optional (in-document)
UI/Monitoring	✅ Rich UI	✅ Rich UI	✅ Rich UI	🟡 Basic via logs
Best for	Enterprise workflows	Batch data pipelines	Modern data workflows	Lightweight, open-source, portable workflow definitions

The Core Difference

Temporal/Airflow/Prefect:

"Deploy a workflow platform, then deploy your workflows to it."

You need servers, databases, monitoring, and operational overhead.

Stof:

"The workflow IS a document. Execute it wherever you need."

No platform required. The workflow is portable data. Open-source.

The Bottom Line

Use Temporal when:

• You need mission-critical workflow durability

• Workflows run for days/weeks/months

• Your team needs rich monitoring and debugging

• You can afford the infrastructure and operational overhead

Use Airflow when:

• You're building batch data pipelines

• You need scheduling and backfill capabilities

• Your team is familiar with Python DAGs

• You need extensive plugin ecosystem

Use Prefect when:

• You want modern workflow orchestration

• You prefer Python-native flows over DAGs

• You want easier setup than Airflow

• You're okay with cloud-hosted or self-hosted server

Use Stof when:

• You need lightweight, open-source, portable workflows

• Workflows are simple to medium complexity

• You don't want to manage infrastructure

• You need workflows as API payloads

• You're building edge/IoT/embedded systems

• Cost and simplicity matter more than rich monitoring

Use Multiple when:

• You need Temporal/Airflow's orchestration + Stof's portability

• Core workflows in Temporal, transformation logic in Stof

• Large-scale scheduling (Airflow) + lightweight execution (Stof)