Best Proxies for Web Scraping
in 2026

Web scraping without proxies is effectively impossible at scale in 2026. Every major website deploys some form of bot detection, and even small sites use services like Cloudflare that automatically challenge or block repeated requests from a single IP address. Without proxies, your scraper gets blocked after 50-100 requests on most protected sites.

The reason is straightforward: websites track incoming IP addresses and apply rate limits, behavioral analysis, and fingerprinting to identify automated traffic. When a single IP makes hundreds or thousands of requests in a short period, it triggers defenses that range from CAPTCHAs to hard IP bans. Proxies solve this by distributing your requests across many IP addresses, making your scraper appear as many different users rather than one bot.

The real question is not whether you need proxies for scraping, but which type of proxy gives you the best balance of cost, success rate, and speed for your specific targets. The proxy market in 2026 offers four distinct categories, each with fundamentally different characteristics. Choosing the wrong type wastes money and produces unreliable data. Choosing the right type can make the difference between a 40% success rate and a 95% success rate.

Each proxy type comes from a different source, carries a different trust level with target websites, and suits different scraping scenarios. Understanding these differences is the foundation of building cost-effective scraping infrastructure.

The following table compares all four proxy types across the metrics that matter most for web scraping: success rate, speed, cost, pool size, best target sites, anti-bot bypass capability, and anonymity level. Data reflects 2026 market conditions and testing.

We compared four leading proxy providers that scraping teams commonly use. Each is evaluated on pricing per GB, success rate, protocol support, geographic coverage, and anti-bot bypass effectiveness. Mobile proxies are positioned as the best choice for heavily protected sites.

Our recommendation for scraping teams: Use mobile proxies from Proxies.sx for heavily protected targets (Cloudflare, DataDome, PerimeterX). The $4-6/GB pricing is competitive with residential proxies while delivering significantly higher success rates. For bulk scraping on low-protection sites, pair mobile proxies with cheaper datacenter proxies to optimize your total cost.

The four major anti-bot systems you will encounter in 2026 are Cloudflare, DataDome, Akamai Bot Manager, and PerimeterX (now HUMAN). Each uses different detection techniques, but they all share one weakness: they cannot aggressively block mobile carrier IP ranges without causing massive collateral damage to real users. This is why mobile proxies consistently outperform other proxy types.

Key insight: The common thread across all anti-bot systems is that they treat mobile carrier IPs with higher trust than any other IP type. This is not a bug in their systems. It is a fundamental limitation: mobile carriers use CGNAT (Carrier-Grade NAT) to share a single public IP among thousands of devices. Blocking that IP would break service for all those devices. Anti-bot vendors know this, and it is why mobile proxies remain the most reliable bypass method. Test your specific targets using the Proxy Tester.

A production scraping system is more than just proxies. You need a headless browser for JavaScript-heavy sites, intelligent rotation logic to distribute requests across IPs, retry mechanisms for failed requests, and a data pipeline to store and process results. Here is how these components fit together.

  Scraping Infrastructure Architecture
  =====================================

  +------------------+     +-------------------+     +------------------+
  |                  |     |                   |     |                  |
  |   Scraper App    |---->|   Proxy Router    |---->|  Target Website  |
  |   (Scheduler)    |     |   (Rotation)      |     |                  |
  |                  |     |                   |     +------------------+
  +--------+---------+     +--------+----------+
           |                        |
           v                        v
  +------------------+     +-------------------+
  |                  |     |                   |
  |  Headless Browser|     |   Proxy Pool      |
  |  (Playwright/    |     |                   |
  |   Puppeteer)     |     |  +-------------+  |
  |                  |     |  | Mobile 4G/5G |  |  <-- Protected sites
  +------------------+     |  | (Proxies.sx) |  |
                           |  +-------------+  |
           |               |  +-------------+  |
           v               |  | Residential  |  |  <-- General scraping
  +------------------+     |  +-------------+  |
  |                  |     |  +-------------+  |
  |   Retry Queue    |     |  | Datacenter   |  |  <-- Low-protection
  |   (Failed reqs)  |     |  +-------------+  |
  |                  |     |                   |
  +--------+---------+     +-------------------+
           |
           v
  +------------------+     +-------------------+
  |                  |     |                   |
  |   Data Pipeline  |---->|   Storage (DB)    |
  |   (Parse/Clean)  |     |                   |
  |                  |     +-------------------+
  +------------------+

For a detailed guide on building this architecture with Python, see our Python Web Scraping with Mobile Proxies Guide. For Cloudflare-specific bypass strategies, read How to Bypass Cloudflare with Mobile Proxies in 2026. Full API documentation is available in our docs.

Proxy costs can escalate quickly at scale. A scraping operation making 1 million requests per day at 100KB average response size consumes roughly 100GB of bandwidth per day. At $6/GB that is $600/day or $18,000/month. Smart optimization can reduce this by 30-50% without sacrificing data quality.