Evaluating Workflow Orchestration Frameworks

python azure temporal orchestration distributed-systems

Key Learnings

Deterministic replay is critical for fault recovery in production systems
Multi-service architecture patterns vary significantly across frameworks
Local dev experience directly impacts iteration speed and debugging

The Approach

Implemented the same invoice processing workflow (PDF → parse → fan-out/fan-in → aggregate) across all three frameworks for an apples-to-apples comparison.

Trade-offs

Each framework trades off different things—replay mechanisms, vendor lock-in, operational complexity, and developer experience all factor into the decision.

Full comparison on Notion: Read the detailed analysis

GitHub repo: View the code