We've all been there. You write a simple script to process a JSON or CSV file. It works perfectly on your machine with a 100KB test file. Then, you deploy it to production, a 2GB file hits the server, and BAM: FATAL ERROR: Ineffective mark-compacts near heap limit Allocation failed - JavaScript heap out of memory. Node.js is incredibly fast, but its default "load-everything-into-memory" approach is a ticking time bomb for ETL (Extract, Transform, Load) tasks. Today, I’m introducing Data-Genie 🧞‍♂️ - a streaming-first ETL engine for TypeScript designed to make massive data processing boringly stable. The Problem: The "Array.map()" Trap Most developers process data like this: const data = JSON . parse ( fs . readFileSync ( ' huge-file.json ' )); // ❌ Memory spikes here const processed = data . map ( record => transform ( record )); // ❌ Memory doubles here fs . writeFileSync ( ' output.json ' , JSON .…