ScrapingAnt alternatives compared: what to pick and why
ScrapingAnt bundles headless Chrome rendering and rotating residential proxies behind one endpoint. It has a generous recurring free tier and no concurrency cap. For light or moderately protected sites, that covers a lot of ground. Teams usually start comparing alternatives once they point it at heavily protected domains, or once their credit usage grows faster than their page count.
Why people switch
Success on protected sites: independent benchmarks put it below half of requests returning usable data on hard targets.
Speed: responses on protected pages can take around half a minute.
Credit math: a full browser request with JS rendering and residential proxies costs over a hundred times a basic call.
Ecosystem: it has fewer integrations and a smaller community than the larger players.
What to compare
Look at success rate on the sites you actually target, average latency and the pricing model. The main pricing models are flat per request, credits with multipliers, bandwidth-based and pay-for-success. Proxy pool size, CAPTCHA handling, compliance certifications and how you get structured data out of the HTML also matter.
The main alternatives
Bright Data
It has the largest residential network, a benchmark success rate close to 100% and hundreds of prebuilt scrapers for big domains. It bills only for successful requests and holds full enterprise compliance. The tradeoff is premium pricing for small teams.
Scrape.do
This one is built for latency, with responses typically under five seconds and a success rate near the top of the list. It offers Markdown output and a permanent free tier. It has no prebuilt scrapers, so parsing is your job.
Zyte
Zyte comes from the team behind Scrapy and offers ML-based structured extraction without selectors. It is strong on protected sites, but costs are harder to predict on difficult targets.
ScrapingBee
ScrapingBee is developer friendly and has an AI extraction mode. JS rendering multiplies credits several times, and stealth proxies multiply them dozens of times, which makes budgets hard to plan.
Apify
Apify is a full automation platform with a marketplace of tens of thousands of community actors, scheduling and integrations. Quality varies from actor to actor, and residential proxy bandwidth is billed separately.
The gap most of these share
Unblocking gets you HTML. It does not get you a clean table. Every API above either hands you raw markup, relies on a prebuilt scraper existing for your site, or adds AI parsing on top. Parsing is still listed across the industry as the part that needs ongoing maintenance.
Minexa.ai approaches this from the extraction side. It is a Chrome extension for anyone who needs structured data, no code required. You open a page and confirm the block that holds the data. Minexa.ai then builds a scraper for that page structure in a few minutes and names every field automatically. Extraction is deterministic and tied to page elements, so a missing value comes back empty instead of guessed. The same scraper also works on structurally similar pages. JavaScript rendering, CAPTCHA and anti-bot handling are built in.
Install the Minexa.ai Chrome extension to try it on a page you already scrape.
Creating a list scraper
Open the page where the full list is already visible.
Click Advanced Scenarios, then List Mode.
Click Continue.
Check the highlighted list and that the row count makes sense, or click Next to pick another area.
Click Create Scraper and wait up to two minutes.
Click Complete Configuration and then Complete Setup to save the job.
Quick decision table
Need | Good fit |
Hardest anti-bot targets, enterprise compliance | Bright Data |
Low latency, simple per-request cost | Scrape.do |
Scrapy teams, ML extraction | Zyte |
Easy integration, moderate protection | ScrapingBee |
Multi-step workflows and orchestration | Apify |
Structured data from any site without code or prebuilt scrapers | Minexa.ai |
Pick your unblocking layer based on your hardest target. Then check how much parsing work it leaves you. Our getting started guide walks through a first dataset in under ten minutes.
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