Changelog

Rate limiting is built in: configure token buckets, sliding windows, or adaptive limits that respond to backpressure.

Metrics are published to standard formats (Prometheus, CloudWatch, DataDog) with zero configuration.

stream.on('*.created', async (event) =>  await db.insert('events', event); ,  concurrency: 50 );

Batching is automatic—control it via `batch(100)` or `batch({ size: 50, timeoutMs: 1000 })` to trade latency for throughput.

Changelog

Error handling is explicit: catch failures at any stage, log them, and route bad events to a dead-letter queue without stopping the main pipeline.

const throttled = stream.throttle( rps: 100, burst: 200 ); const deduplicated = stream.dedup( key: 'event.id', window: 60000 );

Batching is automatic—control it via `batch(100)` or `batch({ size: 50, timeoutMs: 1000 })` to trade latency for throughput.