Node.js Async Iterators Vs Streams FAQ & Answers

Readable Streams (event-based, push model): Event-driven API - stream.on('data', chunk => {}), stream.on('end', () => {}), stream.on('error', err => {}). Manual backpressure - stream.pause() when consumer overwhelmed, stream.resume() when ready. Composable via piping - source.pipe(transform).pipe(destination) automatically handles backpressure/errors. Async Iterators (async/await-based, pull model): for-await-of syntax - for await (const chunk of stream) { await process(chunk); }. Automatic backpressure - loop doesn't pull next chunk until await completes (consumer controls pace). try-catch error handling works naturally. Example: for await (const chunk of fs.createReadStream('file.txt')) { await db.write(chunk); } (Node.js streams are async iterables).

Use Streams for: (1) Node.js I/O (fs.createReadStream, http.IncomingMessage, process.stdin), (2) Complex transform pipelines (compression, encryption, parsing), (3) Need events (progress tracking, custom events), (4) High-performance scenarios (streams ~10-20% faster for large data), (5) Existing ecosystem (most Node.js I/O is stream-based). Use Async Iterators for: (1) Simpler async data processing (database cursors, paginated APIs), (2) Easier error handling (try-catch vs error event), (3) Custom async data sources without stream boilerplate, (4) Readability > raw performance (cleaner code for business logic).

Interoperability (Node.js 18+): (1) Stream → Async Iterator: All streams are async iterables - use for-await-of directly. Example: for await (const chunk of fs.createReadStream('file.txt')) { process(chunk); }, (2) Async Iterator → Stream: Readable.from(asyncIterable) converts generator to stream. Example: Readable.from(queryDB()).pipe(res), (3) Web Streams: ReadableStream (web standard) also supports async iteration. Custom generators: async function* fetchPages(url) { let page = 1; while (page <= 10) { yield await fetch(${url}?page=${page++}); } }.

Performance (2025): Streams 10-20% faster for large data (optimized buffer management, less async overhead), async iterators more maintainable (fewer bugs). Node.js 20+ improvements: Better stream/async iterator interop, full ReadableStream (WHATWG) support, composable transform streams. Best practices: (1) Streams for I/O, async iterators for business logic, (2) Always handle errors (streams: error event, iterators: try-catch), (3) Implement backpressure (avoid memory leaks), (4) Use pipeline() for error propagation: pipeline(source, transform, destination, err => {}).

Readable Streams (event-based, push model): Event-driven API - stream.on('data', chunk => {}), stream.on('end', () => {}), stream.on('error', err => {}). Manual backpressure - stream.pause() when consumer overwhelmed, stream.resume() when ready. Composable via piping - source.pipe(transform).pipe(destination) automatically handles backpressure/errors. Async Iterators (async/await-based, pull model): for-await-of syntax - for await (const chunk of stream) { await process(chunk); }. Automatic backpressure - loop doesn't pull next chunk until await completes (consumer controls pace). try-catch error handling works naturally. Example: for await (const chunk of fs.createReadStream('file.txt')) { await db.write(chunk); } (Node.js streams are async iterables).

Use Streams for: (1) Node.js I/O (fs.createReadStream, http.IncomingMessage, process.stdin), (2) Complex transform pipelines (compression, encryption, parsing), (3) Need events (progress tracking, custom events), (4) High-performance scenarios (streams ~10-20% faster for large data), (5) Existing ecosystem (most Node.js I/O is stream-based). Use Async Iterators for: (1) Simpler async data processing (database cursors, paginated APIs), (2) Easier error handling (try-catch vs error event), (3) Custom async data sources without stream boilerplate, (4) Readability > raw performance (cleaner code for business logic).

Interoperability (Node.js 18+): (1) Stream → Async Iterator: All streams are async iterables - use for-await-of directly. Example: for await (const chunk of fs.createReadStream('file.txt')) { process(chunk); }, (2) Async Iterator → Stream: Readable.from(asyncIterable) converts generator to stream. Example: Readable.from(queryDB()).pipe(res), (3) Web Streams: ReadableStream (web standard) also supports async iteration. Custom generators: async function* fetchPages(url) { let page = 1; while (page <= 10) { yield await fetch(${url}?page=${page++}); } }.

Performance (2025): Streams 10-20% faster for large data (optimized buffer management, less async overhead), async iterators more maintainable (fewer bugs). Node.js 20+ improvements: Better stream/async iterator interop, full ReadableStream (WHATWG) support, composable transform streams. Best practices: (1) Streams for I/O, async iterators for business logic, (2) Always handle errors (streams: error event, iterators: try-catch), (3) Implement backpressure (avoid memory leaks), (4) Use pipeline() for error propagation: pipeline(source, transform, destination, err => {}).