In e-commerce data collection scenarios, ScrapeStorm and Octoparse, as representatives of no-code tools, both support visual operations and dynamic content scraping. However, their core differences lie in their technical architecture, usage costs, and functional focuses. The following comparative analysis is conducted from three dimensions:
I. Technical Architecture and Deployment Flexibility
ScrapeStorm adopts a local deployment model, supporting Windows/MacOS/Linux systems, making it suitable for medium to large teams requiring cross-platform operation. Its AI-driven intelligent mode can automatically identify fields such as product information, prices, and reviews. Tests show a 98.7% success rate in scraping 10,000 product data entries from a certain e-commerce platform.
Octoparse, on the other hand, primarily uses a pure cloud deployment, scraping page elements through a browser plugin and supporting JavaScript rendering and pagination navigation. Its advantage lies in its stronger stability when handling complex website structures (such as iframe nesting and Ajax loading). A 3C merchant used its preset template function to reduce the competitor's price monitoring cycle from 48 hours to 15 minutes.
II. Cost and Functionality Balance
ScrapeStorm's free version limits data export to 100 rows per day, while the professional version starts at $49 per month and offers export in multiple formats including CSV/XLSX/Google Sheets, scheduled tasks, and a proxy IP pool. Its flowchart mode supports simulated mouse movements and conditional statements; a cross-border e-commerce company used this feature to achieve real-time scraping of Amazon's "Buy Box" prices and seller information.
Octoparse's free version supports 10 tasks and 50,000 data entries per month (desktop only), while the standard version costs $99 per month to unlock cloud services and a pre-set template library. Its core value lies in handling highly complex websites (such as dynamic CAPTCHAs and login-state maintenance); a home appliance brand increased its inventory turnover rate by 22% using its scheduled scraping function.
III. Scenarios for ScrapeStorm:
Scenarios requiring quick mastery of AI-powered web scraping, such as e-commerce product information collection and social media review analysis.
Scenarios with limited budgets and moderate data volumes (<10,000 scraped records per day).
Scenarios relying on multi-format export and cross-platform collaboration.
Scenarios requiring Octoparse:
Scenarios needing to handle complex anti-scraping mechanisms (such as CAPTCHAs and login status) or large-scale data (>50,000 scraped records per day).
Scenarios prioritizing high stability and efficient pre-set templates, such as financial data monitoring and multi-platform price comparison.
Scenarios willing to pay a premium for cloud services and advanced features.
IV. Key Decision Points
If efficiency is prioritized, Octoparse's pre-set templates and ability to handle complex websites can save 30% of configuration time. If cost is a concern, ScrapeStorm's free and low-priced professional versions are more suitable for small and medium-sized teams. A test by a beauty brand showed that ScrapeStorm cost 40% less to collect 100,000 user reviews than Octoparse, but Octoparse had a 25% higher success rate when scraping a bank's website due to its support for multi-step login.
Final recommendation: Choose ScrapeStorm for basic e-commerce data collection, and Octoparse for complex scenarios and large-scale data. Both can be integrated with data analysis systems via API, but Octoparse has a more complete developer ecosystem, while ScrapeStorm has a higher degree of AI automation.
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