companies of all sizes
Pick Scrapliy once you're tracking multiple sources, need JS rendering, or want price history without babysitting a script.
Build in-house if you have one or two simple sources and spare engineering time to own breakage.
Scrapliy vs In-House Scraper: Key differences
Most teams that need product or content data from other sites start by writing a script. It works for one site. The costs show up when you add the second, fifth, and twentieth site: proxy rotation, headless rendering for JS-heavy storefronts, bot-block detection, schema drift, and someone on call when a site redesign breaks your parser at 2am.
| Feature | In-House Scraper | Scrapliy |
|---|---|---|
| Time to first data | Days to weeks | Minutes |
| JS-rendered sites | You build/maintain a browser pool | Handled automatically |
| Login-gated sources | Custom auth code per site | Encrypted credentials + session reuse |
| Ongoing maintenance | Your team, indefinitely | Included |
| Cross-source product matching | Build it yourself | Built in (Entity Engine) |
When to choose each approach
When building in-house makes sense
If you're monitoring one or two simple, mostly-static sites and have an engineer who can own it as a side responsibility, a small script is genuinely the right call — don't buy a platform for that.
- One or two sources, low change frequency
- You already have scraping infra from another project
- No need for cross-source product matching or price history
When it stops being cheap
The real cost of in-house scraping is maintenance, not the initial script: sites change their HTML, add bot detection, move to client-side rendering, and gate pricing behind login. Every one of those is an on-call incident if you built it yourself.
- Headless browser pool for JS-rendered storefronts
- Bot-block / soft-block detection so you don't silently ingest garbage
- Login-gated wholesale/B2B sites needing session management
- Cross-source entity resolution once you track more than one competitor per product
What a managed platform buys you
Scheduled crawls, change detection, structured export formats, and a fetch chain that already handles the common failure modes (rate limiting, JS rendering, cookie-gated pages) are infrastructure work you don't have to own.
Scrapliy vs In-House Scraper: Full comparison matrix
A complete feature overview across both options.
| Feature | In-House Scraper | Scrapliy |
|---|---|---|
| Time to first data | Days to weeks | Minutes |
| JS-rendered sites | You build/maintain a browser pool | Handled automatically |
| Login-gated sources | Custom auth code per site | Encrypted credentials + session reuse |
| Ongoing maintenance | Your team, indefinitely | Included |
| Cross-source product matching | Build it yourself | Built in (Entity Engine) |
Frequently asked questions
Everything you need to know about this comparison.