Oxylabs Review 2026 - Proxies and Web Scraper API

Oxylabs is one of the major players in the proxy and web scraping space, offering a large proxy network alongside dedicated scraping APIs. They cater primarily to enterprise clients and large-scale data collection operations.

Key Features

• 100M+ proxy pool including residential, datacenter, and mobile IPs
• Web Scraper API with built-in parsing for popular targets
• SERP Scraper API for Google, Bing, and other search engines
• E-Commerce Scraper API for Amazon, Walmart, and more
• Real-time and batch scraping modes
• Dedicated account managers for enterprise clients

Pricing

Oxylabs is positioned as a premium service. Residential proxies start at $8/GB with a $300 monthly minimum. Their Scraper APIs start at around $49/month. While quality is high, the entry price is steep for individual developers. For a more accessible starting point, ScraperAPI offers similar capabilities from $49/month with no minimum commitments.

Code Example

Using Oxylabs Web Scraper API:

import requests

payload = {
    "source": "universal",
    "url": "https://example.com/products",
    "render": "html"
}

response = requests.post(
    "https://realtime.oxylabs.io/v1/queries",
    auth=("USERNAME", "PASSWORD"),
    json=payload
)

data = response.json()
print(data["results"][0]["content"])

Performance

Oxylabs delivered a 98.3% success rate in our benchmarks. Response times were competitive at 3-5 seconds for rendered pages. Their dedicated datacenter proxies were particularly fast for high-volume, latency-sensitive workloads.

Drawbacks

• High minimum spend ($300/month for residential proxies)
• Complex product lineup can be confusing
• Enterprise-focused pricing does not suit small teams

Verdict

Oxylabs is a strong enterprise option with a massive proxy pool and specialized scraping APIs. However, for most developers, the high entry price is a barrier. We recommend starting with ScraperAPI or ScrapingAnt for their simplicity and affordability, and evaluating Oxylabs when your needs grow to enterprise scale.