Most teams still scrape websites with brittle Python scripts. That's a mistake.
Web scraping via Python scripts is like digging a well with a spoon. It works, but wastes time, breaks with every HTML change, and requires devs constantly patching it.
Apify is different. *It lets you build, test, and scale scrapers without that pain*.
4,000+ developers across Spain, UK, and Europe already use Apify. Not because it's pretty. Because *they save 20-30 hours monthly on maintenance* and can scale to millions of URLs without managing infrastructure.
What Apify actually is
Apify is a web automation platform with three layers:
→ Visual Builder: Drag-and-drop tool for no-code scrapers
→ SDK (Node.js/Python): For devs needing custom logic
→ Cloud Infrastructure: Run your scrapers at scale (50 URLs/second, or 50,000/day without touching anything)
Critical part: *Apify handles proxies, retries, bot detection, and scales automatically*. You write logic once.
Contrast: how other alternatives work
❌ Pure Python scripts → Constant maintenance, fragile to changes, max ~1,000 URLs/day per machine, manage proxies yourself
❌ Legacy RPA tools (UiPath, Blue Prism) → Expensive (€50,000+ annually), slow deployment (6-12 weeks), overkill for web scraping
❌ Pure data APIs (third-party web servers) → Expensive per request, limited data, depends on third parties keeping data fresh
✅ Apify → €30-300/month (volume dependent), deploy in minutes, scale without extra code, data always fresh
Getting started in 15 minutes
Step 1: Basic setup
Go to apify.com, create account (includes 10 free credits, ~€15 value).
Download Apify CLI:
That creates a Node.js project ready with Apify SDK.
Step 2: Write your first scraper
Open src/main.js. Default template gives you this:
That scrapes 1 URL, extracts title and price, saves to Dataset.
Run locally:
In 10 seconds you see results in storage/datasets/default.
Step 3: Scale to 100,000 URLs
Change this:
Deploy to cloud:
Apify runs your scraper in parallel (50-100 simultaneous URLs, depends on plan). Completely transparent.
Cost: ~€50-100 per 100,000 URLs (includes infrastructure, proxies, retries).
Real cases where Apify shines
1. Competitive price monitoring
Spanish marketplace needed to monitor competitor prices every 6 hours.
Without Apify: Cron job + Python script. Broke every 2 weeks when competitors changed HTML. Dev spent 15h/month fixing.
With Apify: Set up once, automatically scales to 10,000 products/day. Maintenance: zero.
Monthly savings: 60h of dev time (~€1,200 in opportunity cost).
2. Lead generation and B2B scraping
Marketing agency needed to extract contacts from directories.
Apify solution: Custom scraper + Zapier integration.
Result: 5,000 leads/month automatically. Sales pipeline grew 40%.
Cost: €150/month on Apify.
3. Real estate
Many Spanish property portals (Idealista, Fotocasa) have limited or expensive APIs.
With Apify: Scraper running every hour, extracts new listings, prices, photos.
Integration: Webhook → custom API → frontend in real-time.
AI agent integration (the future)
Here's where Apify becomes *truly powerful*.
You can pipe Apify output directly to Claude or GPT-4:
That gives you: *automatic scraping + AI analysis + all in 1 pipeline*.
Not theory. Teams using Apify + Claude are doing this already.
Pricing and ROI calculation
Apify uses credit model:
→ Free plan: 10 credits/month (~€15 value). Good for testing.
→ Pay as you go: €1 per 1,000 page views. Minimum ~€5/month.
→ Team (recommended for startups): €99/month + €0,50 per 1,000 extra page views.
Real ROI example:
Suppose you need to scrape 500,000 URLs/month:
- Apify cost: ~€250/month
- Dev cost (maintaining Python script): 20h/month × €50/h = €1,000/month
- Net savings: €750/month or €9,000 annually
You break even on Apify in 10 days.
When NOT to use Apify
❌ If you have direct access to official APIs (use APIs, always better)
❌ If you only scrape 10 URLs once a month (local Python faster to setup)
❌ If you need real-time processing < 100ms (Apify adds ~500ms latency)
✅ Use Apify when: recurring scraping, +100 URLs/week, need low maintenance, want scale without infrastructure.
Common mistakes to avoid
- Ignoring rate limiting: Apify handles retries automatically, but if the website has aggressive throttling, you need delays. Set
navigationTimeoutSecs: 30if websites are slow. - Not using proxies: For scraping at scale, proxies are CRITICAL. Apify includes them by default (€5-20/month extra depending on volume). Without them, your IP gets banned at 100 URLs.
- Unstructured datasets: Design your data schema BEFORE scraping. 100,000 bad URLs = garbage data. Use TypeScript if you can.
Quick alternatives (2026)
→ Bright Data (formerly Luminati): Better for pure proxies, more expensive (€500+/month)
→ Octoparse: More visual than Apify, less flexible with SDK
→ ScrapingBee: Simpler SaaS, worse for complex workflows
→ Puppeteer + your server: Free but requires dev + ops
Verdict: Apify is the best cost/flexibility balance for teams needing scale + low maintenance.
Bottom line: stop scraping with brittle scripts
*Apify turns web scraping from a fragile technical task into an automated asset*.
Not perfect for everything (direct APIs still beat it when they exist). But if you're:
- Spending >10h/month maintaining Python scripts
- Scraping >10,000 URLs/week
- Wanting to integrate scraped data with AI agents
Apify is the answer. Setup in 15 minutes, cost <€300/month even at large scale, zero infrastructure.
Start with the free tier today. In 3 days you'll know if it saves you time.
