iPaaS on AWS vs Azure
Both AWS and Azure offer a complete, production-proven integration stack — APIs, events, queues, workflows, and observability — capable of replacing a commercial iPaaS. The right choice is decided by where your workloads, identity, and skills already live, and by a handful of architectural differences that matter at enterprise scale.
The Two Stacks, Side by Side
| Capability | Azure | AWS |
|---|---|---|
| API management | API Management (APIM) | API Gateway (+ AppSync) |
| Event routing | Event Grid | EventBridge |
| Queues & pub/sub | Service Bus (queues, topics, sessions) | SQS + SNS |
| High-volume streaming | Event Hubs (Kafka-compatible) | Kinesis / MSK |
| Workflow orchestration | Logic Apps, Durable Functions | Step Functions |
| Serverless compute | Azure Functions | Lambda |
| SaaS connectivity | 1,000+ Logic Apps connectors | EventBridge partner sources, AppFlow |
| Observability | Application Insights + Log Analytics | CloudWatch + X-Ray |
The Differences That Change Designs
Both sets satisfy the Well-Architected pillars of their respective clouds. But these differences matter:
Connector Philosophy
Azure's Logic Apps connector catalog is the closest thing to a classic iPaaS experience — a genuine advantage for landscapes dominated by Microsoft 365, Dynamics, SAP, and mainstream SaaS. AWS takes a composition approach: fewer packaged connectors, more building blocks.
Messaging Semantics
Service Bus offers sessions (per-key ordering), transactions, and dead-lettering in one enterprise-grade service. On AWS, you compose SQS FIFO, SNS, and EventBridge to reach similar guarantees; each piece is excellent, but the design burden sits with your architects.
Workflow Style
Logic Apps is visual-first with a low-code entry point; Step Functions is definition-first (JSON/CDK) with outstanding express-workflow economics at massive scale. Teams tend to strongly prefer whichever matches their culture.
Identity & Governance Gravity
If your users, security groups, and conditional access live in Entra ID, Azure integration inherits it natively. If your organization runs on AWS Organizations, SCPs, and IAM, the same logic points the other way. Governance gravity is usually the silent tiebreaker.
Decision Logic
Integration follows the workloads.If 80% of your endpoints, data, and engineers are on one cloud, put the integration backbone there — cross-cloud latency, egress fees, and split observability are taxes you pay forever. Multi-cloud enterprises should place the backbone with the systems of record (usually the ERP side).
Reference Architectures
Notice what is identical across both: an API layer for questions, an event backbone for facts, workflow for orchestration, dead-letter handling, and end-to-end tracing. The architecture patterns are cloud-portable; only the service names change.
Azure Flavor
AWS Flavor
Frequently Asked Questions
Can we run one integration platform across both clouds?
Technically yes, practically expensive. Prefer one backbone plus governed API/event bridges to the other cloud over a symmetric dual platform.
Which is better for a Boomi exit?
Whichever cloud hosts your landing zone and skills. See our Boomi migration guide for the mapping tables and phased plan on both.
What about Kafka?
Both clouds accommodate it (Event Hubs' Kafka protocol support; MSK on AWS). We recommend it when the ecosystem tooling — Connect, Streams, schema registry — is genuinely needed, not as a default.
Choose With an Architecture, Not a Brochure
Book an integration backbone selection workshop — you'll get a decision matrix scored for your landscape, a reference architecture on your chosen cloud, and a costed 90-day implementation plan.
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