Top 5 Web Scraping APIs: Which One Actually Delivers?

If you're hunting for a web scraping tool that won't let you down halfway through a project, you're probably tired of marketing fluff. Let's cut through it. We tested five popular APIs on real targets—Amazon, Google, and Idealista—running 50 requests each to see what actually works.

When you're building something that depends on reliable data extraction, you need more than promises. You need proof that an API can handle anti-bot systems, deliver consistent speeds, and not drain your budget. That's exactly what this breakdown gives you: hard numbers on success rates, response times, and per-request costs across platforms that fight scrapers for a living.

Whether you're pulling product data, tracking search rankings, or monitoring real estate listings, the API you choose determines if your project thrives or dies at scale. The web scraping industry is packed with options—some excel at specific use cases, others crumble under pressure. Here's what happened when we stress-tested them.

Testing Setup: How We Measured Performance

We ran identical Python scripts against each API, targeting three notoriously difficult websites. Each test involved 50 randomized requests per platform, measuring success rates (did it work?), average response times (how fast?), and cost efficiency (what's the damage per request?).

The domains chosen represent different challenges: Amazon's aggressive bot detection, Google's constantly evolving defenses, and Idealista's regional anti-scraping measures. If an API can't handle these consistently, it won't survive production environments.

1. Scrapingdog: The Budget Champion

Scrapingdog hit 100% success rates across all three platforms. Response times averaged 7.97 seconds for Amazon, 2.96 for Google, and 2.71 for Idealista. At roughly $0.000067 per request, it's the most economical option that doesn't compromise reliability.

The dashboard is straightforward—even non-developers can configure requests. You get 1,000 free credits to test everything, and the documentation assumes you want to build something fast, not spend days deciphering API quirks. Dedicated APIs for Amazon, Google, and other major platforms return parsed JSON, saving you extraction headaches.

Customer support responds in minutes, not days. When you're dealing with scraping infrastructure that's mission-critical, response speed from the vendor matters as much as API response speed.

For teams needing reliable Google scraping at scale without bleeding budget, this is where the data points. Before committing to any provider, though, you should evaluate how different tools handle your specific targets. 👉 Test enterprise-grade scraping infrastructure built for high-volume data extraction to see how alternative architectures compare when reliability becomes non-negotiable.

2. ScraperAPI: Solid but Slower on Google

ScraperAPI delivered 100% success everywhere, but Google response times were brutal—averaging 20.35 seconds. Amazon and Idealista performed better at 8.45 and 3.56 seconds respectively. At $0.0000997 per request, it's competitively priced.

The trial includes a generous 5,000 credits. The dashboard lets you test calls directly without switching contexts, which speeds up debugging. Documentation is thorough, and integration is straightforward—you're not wrestling with authentication quirks or undocumented parameters.

No chat widget, but email support gets back to you reasonably fast. If Google isn't your primary target, ScraperAPI handles other platforms well. But if you're scraping search results at volume, those 20-second delays compound quickly.

3. Scrapingbee: Budget-Friendly with Idealista Issues

Scrapingbee achieved 100% success on Amazon and Google but dropped to 73% on Idealista. Response times hovered around 9.46, 8.45, and 7.58 seconds—consistently slower than competitors. Per-request cost sits at $0.000083, making it economically attractive.

You start with 1,000 trial credits. The documentation is clean, integration is painless, and they offer dedicated Google APIs with parsed JSON output. Support is accessible via chat or email.

The Idealista failure rate is concerning if you're targeting regional or niche sites. For mainstream platforms, it performs adequately, but the slower speeds might bottleneck high-throughput operations.

4. Zenrows: Complete Failure on Idealista

Zenrows managed 74% success on Amazon, 100% on Google, and 0% on Idealista. Response times were 12.84 seconds for Amazon and 7.52 for Google. At $0.00008 per request, pricing is competitive, but success rate inconsistencies are a dealbreaker.

The platform focuses on proxies alongside APIs. You get $1 in free credits (no credit-based system makes cost analysis harder). Documentation is informative, integration is smooth, and support channels include both email and chat.

The complete Idealista failure suggests limited infrastructure for certain geo-targeted or smaller platforms. If your project depends on consistent access across diverse targets, this is risky.

5. Scrape.do: Fastest Amazon Performance

Scrape.do hit 100% success across all platforms with impressive speeds: 6.76 seconds for Amazon (fastest in this comparison), 4 seconds for Google, and 5.96 for Idealista. Cost per request is $0.000071.

Trial starts with 1,000 credits. The API is general-purpose (raw HTML output, no dedicated parsers), so you'll handle extraction yourself. Documentation is excellent, integration is quick, and support responds fast via chat or email.

If raw speed matters and you're comfortable parsing responses yourself, Scrape.do delivers. For teams wanting pre-parsed JSON from dedicated APIs, other options might fit better.

The Numbers Don't Lie: Which API Wins?

Success rate winner: Scrapingdog, ScraperAPI, and Scrape.do all hit 100% on our primary targets.

Speed champion: Scrape.do leads on Amazon (6.76s), while Scrapingdog dominates Google (2.96s) and Idealista (2.71s).

Best value: Scrapingdog offers the lowest cost on Google with perfect reliability. Scrape.do and Scrapingbee compete closely on price, but reliability differences matter at scale.

Avoid for: Zenrows if you need consistent multi-platform coverage. Scrapingbee if Idealista-type regional sites are in scope.

Pick Based on Your Actual Needs

If you're scraping Google at high volume and budget matters, Scrapingdog delivers unmatched speed-to-cost ratio with 100% success. For Amazon-heavy workloads where milliseconds compound, Scrape.do's raw speed wins—just be ready to handle parsing.

ScraperAPI works when Google isn't your primary target and you want generous trial credits to test broadly. Scrapingbee suits mainstream platforms if you can tolerate occasional regional hiccups.

This wasn't about crowning one universal winner—it's about matching tools to real-world requirements. The API that works perfectly for one project might be overkill or underpowered for another. Test against your actual targets before committing, and remember that infrastructure performance matters as much as cost per request when you're moving millions of data points monthly. Understanding how modern scraping solutions balance proxy rotation, headless browsing, and anti-bot evasion determines whether your pipeline scales or stalls. 👉 Explore advanced scraping infrastructure designed for enterprise-scale data collection to see how different architectural approaches handle production workloads.

Choose the API that survives your specific battlefield. Everything else is just noise.