Node.js Streams: A Practical Guide to Processing Large Files Without Memory Issues

Node.js Streams: A Practical Guide to Processing Large Files Without Memory Issues Target: Draft.dev / Honeybadger | ~2,800 words The Problem With "Just Reading the File" Every Node.js developer has written this at least once: const fs = require ( ' fs ' ); const data = fs . readFileSync ( ' bigfile.csv ' ); processData ( data ); It works fine — until it doesn't. The day your CSV grows from 10MB to 10GB, your process crashes with FATAL ERROR: Reached heap limit Allocation failed - JavaScript heap out of memory . You double your server RAM. It crashes again at 20GB. You're fighting the wrong battle. The fix isn't more RAM. It's streams. This guide walks you through Node.js streams from first principles, with a real project you'll build by the end: a pipeline that processes a 5GB server log file, extracts error events, aggregates them by endpoint, and writes a report — all while using under 50MB of RAM. What Streams Actually Are (and Why Node.js Has Four Types) A stream is an abstraction