Both platforms look identical on day one: a schema file, a typed client, a deploy that works. The difference shows up months later, in the queries you cannot afford and the layer you cannot leave. A practical comparison of data models, billing shape, auth stickiness and exit cost.
Most API pipeline failures are green DAGs producing incomplete data. A practical guide to running Apache Airflow on AWS for SaaS and API extraction: choosing between MWAA provisioned, MWAA Serverless and self-managed, the pool setting that silently stops throttling when you go deferrable, retry and pagination design, secrets handling, and the four cost lines that actually move.
Most Shopify dashboards built on AWS work perfectly for about three weeks, then quietly drift away from the numbers in the Shopify admin. Here is why that happens, and how to design the ingestion, storage and query layers so your totals still reconcile six months in.
Jira's built-in reports stop at the board boundary. This guide walks through a Jira analytics pipeline built on AWS Lambda, S3 and Athena, organised around the four failure families that actually bite: the removed search endpoint, silently truncated changelogs, incremental loads that duplicate rows, and an S3 layout that quietly inflates your query bill.
Semantic search finds the most persuasive document, not the earliest one. Here is how to architect an AI construction claims and dispute intelligence platform on AWS so retrieval respects the contractual clock, schedule data stays out of the vector index, every answer resolves to a page, and privileged material never shares a retrieval path with project records.