streams

Node.js streams process large datasets in chunks rather than loading everything into memory. You define Readable, Writable, and Transform streams to build data pipelines that handle file I/O and network data efficiently without exhausting memory limits.

Backpressure in Node.js streams occurs when data ingestion outpaces processing. You handle backpressure by composing streams into pipelines, ensuring the downstream signals upstream to pause, which maintains reliable throughput and prevents memory overflow during transformations.

You build a data pipeline by defining a Readable stream for the data source, a Transform stream for in-flight data transformations, and a Writable stream for the destination. Composing them ensures robust backpressure handling and efficient memory-conscious processing.

Use Node.js streams for large datasets, real-time processing, and continuous data handling. Buffering entire files loads all data into memory simultaneously, whereas streams process data in sequential chunks, making them essential for scalable and memory-efficient file I/O.

Yes, Node.js Transform streams allow real-time data transformations. As data flows through the pipeline, the Transform stream modifies in-flight data between the Readable source and Writable destination, enabling efficient streaming transformations for network I/O and file processing.

Node.js data pipelines crash when processing large files if backpressure is not handled correctly. Without proper stream composition, memory builds up from unmanaged data chunks. Implementing pipeline patterns ensures robust throughput and prevents memory overflow crashes.