5 Best ScrapingBee Alternatives for Web Scraping in 2026

TL;DR

• Choose Firecrawl if you want machine-readable output your model can use immediately.
• Choose Bright Data or Oxylabs if your bottleneck is proxy scale and unblocking.
• Choose Apify if you want a marketplace of ready-made scrapers.
• Choose Octoparse if you want a visual tool and write no code.

We have to tip our hats to ScrapingBee. The team has built quite a capable web scraping API, and for many teams it handles all scraping needs well. But you may still hit a point where credit costs, output format, or the scale cap pushes you to look around. And if you're already there, this guide is for you.

I looked at five ScrapingBee alternatives, the closest competitors in 2026, and tested them myself rather than relying on secondhand reviews, so the numbers here are what I actually saw.

The data is updated as of June 16, 2026.

ScrapingBee is a web scraping API that handles proxies, headless browsers, and anti-bot defenses so you can simply request a page and get its contents back. It's positioned as the web scraping API that prevents you from getting blocked.

The core product is a scraping API that returns the page source by default, with a handful of capabilities layered on top:

• JavaScript rendering in a headless Chrome browser
• Automatic proxy rotation, with premium and stealth residential proxies for harder targets
• Geotargeting and full-page screenshots
• CSS and XPath extraction rules, so you can pull specific fields without parsing the HTML yourself
• AI data extraction via additional parameters (ai_query and ai_extract_rules) for schema-based or prompt-based output
• A Google Search API, plus dedicated Amazon and Walmart endpoints

As of June 2026, the pricing is credit based and plans run from Freelance at $49/mo (250,000 credits, 10 concurrent requests) up to Business+ at $599/mo (8,000,000 credits, 200 concurrent requests), with a free trial of 1,000 credits and no card required.

ScrapingBee's docs say a basic request is cheap, but the premium and stealth proxies you need for tough sites cost far more. A single stealth-proxy call costs 75 credits, so a plan's credits can run out much faster than the advertised number suggests when you scrape hard targets.

Each tool below wins on a different axis: Firecrawl for AI-ready output, Bright Data and Oxylabs for proxy scale, Apify for marketplace automation, and Octoparse for no-code access.

Firecrawl is an open-source context API built for teams that feed live web data into models. Where ScrapingBee returns the page source by default and offers AI extraction as an opt-in layer, Firecrawl's default response is already model-ready Markdown or schema-defined JSON in one call.

• Scrape turns any page into clean Markdown or structured JSON in one call
• Search lets you query the web and get full page content back, not just links
• Interact clicks, fills forms, logs in, and navigates JavaScript-heavy flows
• Crawl and Map pull an entire site or list every URL on a domain
• /monitor watches pages or whole sites and notifies your agent the moment content changes
• Open source, with Python, Node, and REST SDKs and 1,000 free credits per month

On the same JavaScript-rendered page (Hacker News), Firecrawl returned roughly 55% fewer characters and ran about 2.5× faster than ScrapingBee. Here are the exact numbers from that test.

ScrapingBee returned 34,873 characters of raw HTML in about 2.85 seconds, with a response cost of 5 credits for the rendered request. Firecrawl returned the same page as 15,371 characters of clean Markdown in about 1.16 seconds, with the page title already parsed into metadata.

Here is the Firecrawl call that produced the output above:

from firecrawl import Firecrawl
 
firecrawl = Firecrawl(api_key="fc-YOUR-API-KEY")
 
doc = firecrawl.scrape("https://news.ycombinator.com", formats=["markdown"])
print(doc.markdown)

For structured data extraction, you pass a schema and Firecrawl returns JSON directly, with no HTML parsing in between:

schema = {
    "type": "object",
    "properties": {
        "top_stories": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "title": {"type": "string"},
                    "points": {"type": "integer"},
                },
            },
        }
    },
}
 
doc = firecrawl.scrape(
    "https://news.ycombinator.com",
    formats=[{"type": "json", "schema": schema}],
)
print(doc.json)

Output

{
  "top_stories": [
    { "title": "MiMo Code is now released and open-source", "points": 229 },
    { "title": "Lines of code got a better publicist", "points": 271 },
    { "title": "Show HN: Homebrew 6.0.0", "points": 107 }
  ]
}

Both tools rendered the JavaScript page reliably. ScrapingBee's default scrape returns HTML for you to parse or pass to its AI extraction parameters as a follow-on step, while Firecrawl's default already returns parsed Markdown that maps to what you asked for. In this test that was less than half the characters, 15,371 versus 34,873, which means fewer input tokens reach your model on every call. Firecrawl is built to be token efficient, so every call costs less downstream.

Firecrawl uses transparent, credit-based pricing where one credit covers one page.