We're a small team collecting a few thousand pages per week for an ML dataset. Writing the basic scraper in Node isn't the difficult part; the bigger concerns are proxy management, retries, JavaScript-rendered pages, and keeping the system working as target sites change. At this scale, would you build and maintain the scraping infrastructure yourselves, or pay for a managed web-scraping API to reduce maintenance?
3 Answers
Building in-house can make sense if you’ll be scraping large volumes continuously and have the time to operate it. For a small team with limited maintenance bandwidth, a managed service is likely the better starting point. You can always bring the workload in-house later if the recurring cost becomes significant or you need more control.
It depends heavily on the sites and features you actually need. Some targets may work with a simple HTTP client and basic retry logic, so you might not need JavaScript rendering or proxy rotation everywhere. Evaluate the sources individually before paying for a full-featured service.
For a few thousand pages a week, I’d probably use a managed scraping API. The expensive part isn’t writing the initial Puppeteer script—it’s maintaining proxies, retries, browser sessions, and selectors whenever a site changes. Paying for that infrastructure lets the team focus on building the ML dataset instead of constantly repairing the scraper.
A simple internal scraper can be worthwhile when the site is stable and the requirements are narrow. The decision mostly comes down to how often the targets change and whether someone can own the ongoing maintenance.