ScrapingBee alternatives compared for structured data without code
ScrapingBee is a solid scraping API. It renders JavaScript with headless Chrome, rotates proxies, supports geotargeting and lets developers write CSS or XPath extraction rules. For many projects it works fine. But teams often start looking elsewhere once a few practical issues pile up, and the right replacement depends on which issue is hurting most.
This guide compares the main options side by side, then looks at a different approach for people who want clean spreadsheet-style data without writing selectors at all.
Why people look for a ScrapingBee alternative
Credit multipliers. JavaScript rendering and premium or stealth proxies multiply the cost of a single request. Stealth requests can consume dozens of credits each, which makes monthly budgets hard to predict.
Credits reset monthly. Unused credits do not roll over, which is awkward for irregular workloads.
Mostly raw HTML output. Unless you write extraction rules or pay for the AI add-on, you still need to parse the page yourself.
Limited no-code options. Outside of a Make integration, the tool assumes you can code.
Mixed results on heavily protected sites. Success rates drop on aggressive anti-bot setups.
The main alternatives at a glance
ScraperAPI
The closest match in API design. It adds an async API, a scheduling layer for recurring jobs, browser instructions like scroll and click, and dedicated endpoints for large retail and search sites. It tends to be cheaper per page at higher volumes, though average response times run slower.
Apify
A full platform built around a large marketplace of prebuilt scrapers. Good if the site you need already has a maintained scraper. Pricing is based on compute usage, which is harder to forecast, and community scrapers vary in quality.
Firecrawl
Open source and aimed at AI pipelines. It returns Markdown or JSON by default and includes crawling, search and monitoring. Less suited to traditional row-and-column data collection.
Scrapingdog
Positioned on predictable cost, with a small fixed credit range per request regardless of proxy tier or rendering. A common pick for solo developers.
Scrape.do
Focused on speed and success rate, with opt-in parameters instead of default surcharges. There is no built-in extraction engine, so parsing stays on your side.
Bright Data
Enterprise proxy infrastructure with a huge residential network, compliance certifications and prebuilt domain scrapers. Powerful, but expensive and complex for small teams.
Comparison table
Tool | Typical output | Pricing model | No-code |
ScrapingBee | HTML, rule-based JSON | Credits with multipliers | Limited |
ScraperAPI | HTML, endpoint JSON | Credits | No |
Apify | JSON, CSV, Excel | Compute units | Yes, via prebuilt scrapers |
Firecrawl | Markdown, JSON | Credits | No |
Scrapingdog | HTML, JSON | Flat credits | No |
Scrape.do | HTML | Per request | No |
Minexa.ai | JSON, CSV, Excel | Credits | Yes, Chrome extension |
The gap most alternatives leave open
Look at the table again. Almost every option either hands you raw HTML or depends on a scraper someone else already built. If your target site is niche, you are back to writing selectors or waiting for a catalog to catch up.
Minexa.ai takes a different route. It is an AI scraper that runs through a Chrome extension. You open a page, confirm the block of data you want, and Minexa.ai builds a scraper for that page structure in a few minutes. It discovers the fields (called columns) automatically, so there is no XPath, no CSS, and no prebuilt catalog to search. Any site with a consistent layout can become a source.
Extraction is deterministic. Each column is tied to a specific element on the page, so the same page always returns the same values. If a value is missing, you get an empty field rather than a guess. JavaScript rendering, CAPTCHA and anti-bot handling are built in.
Install the Minexa.ai Chrome extension to try it on a page you already need data from.
How to build a list scraper with Minexa.ai
Open a page where the full list is already visible, such as search results or a category page.
Click Advanced Scenarios, then List Mode.
Click Continue.
Check the highlighted list container and that the row count makes sense. Click Next to pick a different section if needed.
Click Create Scraper and wait up to two minutes. All columns appear automatically.
Click Complete Configuration then Complete Setup to save the job and find it later.
For single-item pages like a product or job post, Detail Mode works the same way. Adding three similar URLs during setup improves accuracy. Most people get a first structured dataset within ten minutes.
How to choose
You code and want a drop-in API swap: ScraperAPI or Scrapingdog.
You feed AI pipelines with Markdown: Firecrawl.
Your site has a maintained prebuilt scraper: Apify.
You need enterprise proxies and compliance: Bright Data.
You want structured rows from any site without code: Minexa.ai.
Whatever you pick, test your hardest target site first. Results on a protected page tell you more than any feature list.
FAQ
Do these tools all handle JavaScript and CAPTCHAs? Yes, the major ones do, but success rates vary by site.
Which alternative is easiest to migrate to from ScrapingBee? ScraperAPI and Scrapingdog have the closest API shape.
Do I need a prebuilt scraper with Minexa.ai? No. It creates a scraper for each page structure you select, in minutes.
Ready to see it on your own data? Start with the Minexa.ai get started guide.
Further reading: Prompt-based or point-and-click AI scrapers: how to choose
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