Traditional scraping runs on a fixed schedule: scrape a list of URLs every hour. Event-driven scraping instead triggers jobs in response to meaningful events: a price change webhook from an e-commerce platform, a new listing notification from a marketplace API, a social mention detection, or a message published to a queue by another system.
Event-driven architectures reduce unnecessary scraping by only fetching content when there is evidence it has changed, improving efficiency and reducing target server load. They also enable near-real-time data pipelines: an event triggers a scrape job within seconds, the result is processed and written to the destination, and a downstream consumer is notified — all without a polling loop.
Implementing event-driven scraping requires: an event source (webhook endpoint, Kafka consumer, AWS SQS subscriber), a job dispatcher that converts events to scrape tasks, a scraping backend (HTTP or browser tier), and a delivery mechanism for results (database write, webhook to another system, or message publish).