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Node.js Streams Basics

When should you use Node.js streams instead of buffering entire files in memory?

Answers use simple, clear English.

Quick interview answer

Streams process data chunk-by-chunk for large payloads — uploads, downloads, transforms — keeping memory bounded. Prefer pipeline() for error propagation. Buffering a multi-GB file into a string will OOM.

Detailed answer

Real example & use case

Compressing multi-GB logs to S3 without loading the whole file into RAM.

Pros & cons

Pros: bounded memory. Cons: backpressure and error handling are harder than sync code.

Code example

import { createReadStream, createWriteStream } from 'fs';
import { pipeline } from 'stream/promises';
import { createGzip } from 'zlib';

await pipeline(
  createReadStream('big.log'),
  createGzip(),
  createWriteStream('big.log.gz'),
);

Practice code · javascript (view only · no execution)

import { createReadStream, createWriteStream } from 'fs';
import { pipeline } from 'stream/promises';
import { createGzip } from 'zlib';

await pipeline(
  createReadStream('big.log'),
  createGzip(),
  createWriteStream('big.log.gz'),
);

#nodejs#streams