ScrapingBee vs Octoparse(2026)
ScrapingBee is better for teams that need very simple api — fast to integrate. Octoparse is the stronger choice if no coding required. ScrapingBee is paid (from $49/month) and Octoparse is freemium (from $119/month).
Full feature breakdown, pricing details, and pros & cons below.
By Bikram NathLast updated
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ScrapingBee
ScrapingBee is a developer-focused web scraping API that handles headless browsers, proxy rotation, and CAPTCHA avoidance behind a single endpoint. You send a URL and get back rendered HTML or extracted data — no infrastructure to manage.
Starting at $49/month
Visit ScrapingBeeOctoparse
Octoparse is a no-code, point-and-click web scraping tool that lets non-developers build scrapers visually. It offers cloud extraction, scheduling, IP rotation, and pre-built task templates for popular sites — turning web pages into structured data without writing code.
Starting at $119/month
Visit OctoparseHow Do ScrapingBee and Octoparse Compare on Features?
| Feature | ScrapingBee | Octoparse |
|---|---|---|
| Pricing model | paid | freemium |
| Starting price | $49/month | $119/month |
| Single API endpoint | ✓ | — |
| JavaScript rendering (headless Chrome) | ✓ | — |
| Automatic proxy rotation | ✓ | — |
| Premium + residential proxies | ✓ | — |
| Google search API | ✓ | — |
| AI-powered data extraction | ✓ | — |
| No-block guarantee on credits | ✓ | — |
| Visual point-and-click builder | — | ✓ |
| Cloud-based extraction | — | ✓ |
| Scheduled scraping | — | ✓ |
| IP rotation | — | ✓ |
| Pre-built task templates | — | ✓ |
| Auto-detect data fields | — | ✓ |
| Export to CSV/Excel/database/API | — | ✓ |
ScrapingBee Pros and Cons vs Octoparse
ScrapingBee
Octoparse
Deep dive: ScrapingBee
When to choose ScrapingBee
ScrapingBee is the right choice when the team wants the simplest possible scraping API: a single endpoint that accepts a URL and returns rendered HTML, with proxy rotation and JavaScript execution handled automatically. It fits teams that do not want to manage browser infrastructure, proxy pools, or anti-bot logic, and where the scraping volume is moderate, roughly 10,000 to 500,000 pages per month. The API is stateless and requires no SDK: a simple HTTP GET with the URL and API key returns the page content. This makes it the fastest to integrate into existing codebases. The credit-based pricing is predictable: each request costs 1 credit for basic HTML, 5 credits for JavaScript rendering, and 10 to 25 credits for premium proxies. Choose ScrapingBee when the team needs a drop-in scraping API that works immediately. Avoid it when the volume exceeds 500,000 pages per month where per-credit pricing becomes expensive, or when the team needs scheduling, data storage, or workflow orchestration built into the scraping platform.
Real-world use case
A marketing team at a SaaS startup uses ScrapingBee to monitor competitor pricing pages. A daily cron job in a Next.js API route sends 50 URLs to ScrapingBee's API with JavaScript rendering enabled, parses the returned HTML for pricing table data using Cheerio, and stores the results in Supabase. The entire setup is 40 lines of TypeScript. Each request consumes 5 credits for JS rendering, so the daily cost is 250 credits. On the Freelancer plan at per month with 150,000 credits, the team has ample headroom for growth. The tradeoff: ScrapingBee returns raw HTML, so the team must write and maintain their own parsing logic. Apify or Firecrawl would extract structured data automatically. Additionally, if a competitor site changes its HTML structure, the parsing breaks silently, and the team only discovers the issue when they notice stale data.
Hidden gotchas
Credit consumption varies dramatically based on options selected per request. A basic HTML request costs 1 credit, but enabling JavaScript rendering increases it to 5. Enabling premium proxies on top of JS rendering costs 10 to 25 credits per request. A team that enables both options on all requests will burn through their credit allocation 10 to 25 times faster than one using basic HTML only. The AI data extraction feature, which uses an LLM to extract structured data from HTML, costs additional credits per field extracted. There is no free tier: the trial includes a limited number of credits, and after they are exhausted, a paid plan is required. The Google Search API endpoint costs 5 credits per search and returns SERP results in JSON, but the results are not always identical to what a real browser session returns due to proxy geolocation differences. Rate limiting on the API is not clearly documented for lower-tier plans, and teams that send concurrent requests above the plan limit receive 429 errors without a retry-after header.
Pricing breakdown
The Freelancer plan at per month includes 150,000 credits. The Business plan at per month includes 1,000,000 credits. A team making 10,000 basic HTML requests and 5,000 JavaScript-rendered requests per month consumes 10,000 plus 25,000 equals 35,000 credits, fitting comfortably on the Freelancer plan. The same volume on Apify would cost roughly to in compute units for HTTP-based crawling, making Apify significantly cheaper for high-volume, simple scraping.
Deep dive: Octoparse
When to choose Octoparse
Octoparse is the right choice when the scraping team consists of non-developers who need a visual, point-and-click interface to extract data from websites without writing code. It is strongest for business analysts, marketing teams, and operations teams that need to collect competitor pricing, product catalogs, or lead lists and export the results to Excel or a database. The auto-detect feature attempts to identify data fields on a page automatically, and pre-built task templates for common sites like Amazon, eBay, and Yellow Pages allow extraction to start within minutes. Choose Octoparse when the team has no coding skills and the scraping targets are relatively standard e-commerce or directory pages. Avoid it when the scraping requires custom logic, when the targets use heavy anti-bot protection, or when the team needs an API-first approach that integrates into existing data pipelines.
Real-world use case
A procurement team at a mid-size retailer uses Octoparse to scrape product prices and availability from 15 supplier websites weekly. Each website has a pre-configured task that navigates to the product listing page, paginates through results, and extracts the product name, price, and stock status. The team schedules tasks to run every Monday morning via the cloud scheduler, and results are exported to a shared Google Sheet. The team has no developers and built all 15 tasks using the visual editor in about 2 hours total. The tradeoff: the monthly cost at per month for the Standard plan is higher than API-based tools like ScrapingBee or Firecrawl for the same volume. The team accepts this because they cannot write code and the visual builder eliminates their dependency on engineering.
Hidden gotchas
The pricing structure is confusing: Octoparse lists different prices on different parts of their website, and the actual cost depends on whether the plan is billed monthly, annually, or via the legacy pricing model. The Standard plan at per month includes cloud-based extraction with limited concurrency, and the Professional plan at per month adds more concurrent tasks and advanced features. The desktop application runs on Windows only, which excludes Mac-only teams from local extraction. The cloud extraction service has a queue system that can delay task execution during peak hours, meaning scheduled tasks may not start at the exact configured time. Anti-bot handling is basic compared to Bright Data or Apify: Octoparse rotates IP addresses and adds delays between requests, but sites with sophisticated bot detection like Cloudflare or Akamai will block many extraction attempts. The auto-detect feature works well for simple table-based pages but produces poor results on modern JavaScript-rendered sites with complex DOM structures.
Pricing breakdown
The free plan allows limited local extraction with no cloud features. The Standard plan at per month includes cloud extraction and scheduling. The Professional plan at per month adds more concurrency, advanced scheduling, and API access. A team running 15 scheduled tasks weekly with an average of 500 pages per task, totaling 30,000 pages per month, fits on the Standard plan. For comparison, the same volume on ScrapingBee would cost approximately per month for basic HTML extraction, and on Apify approximately per month using HTTP-based crawlers.
Should You Use ScrapingBee or Octoparse?
For most teams, ScrapingBee is the better default: it offers very simple api — fast to integrate and is paid (from $49/month). Choose Octoparse instead if no coding required matters more than no free tier (trial credits only). There is no universal winner — the right pick depends on your budget, team size, and whether you value very simple api — fast to integrate or no coding required more.
Choose ScrapingBee if…
- •Very simple API — fast to integrate
- •Handles JS rendering automatically
- •Good documentation
Choose Octoparse if…
- •No coding required
- •Friendly for non-developers and analysts
- •Free plan available