Compare Gaffa vs. Scrapy

Gaffa is a REST API built for web scraping and browser automation, allowing developers to run real, full browsers at scale with a single API call. It removes the difficulty of managing headless browser frameworks, rotating proxies, CAPTCHA solving, and scaling infrastructure, all of which are handled automatically. JavaScript-heavy and dynamic websites render exactly as they would for a human visitor by default. Beyond standard scraping, Gaffa supports AI-driven structured data extraction (extract data into a defined schema without writing CSS selectors), screenshot and PDF capture, infinite-scroll and form-filling automation, and clean Markdown conversion for feeding webpages directly into LLM and RAG pipelines. A rotating residential proxy network keeps access reliable across regions, and a credit-based pricing model means teams pay only for the browser time and bandwidth they actually use. Gaffa is designed for AI engineers, data teams, and developers who want production-grade web data extraction without having to build and maintain their own infrastructure.

Scrapy is a high-level framework designed for fast web crawling and scraping, enabling users to navigate websites and retrieve structured data from their content. It serves a variety of applications, including data mining, web monitoring, and automated testing. The framework comes equipped with advanced tools for selecting and extracting information from HTML and XML documents, utilizing enhanced CSS selectors and XPath expressions, as well as providing convenient methods for regular expression extraction. Additionally, it supports generating feed exports in various formats such as JSON, CSV, and XML, with the capability to store these outputs in diverse backends including FTP, S3, and local file systems. Scrapy also features robust encoding support that automatically detects and handles foreign, non-standard, and broken encoding declarations, ensuring reliable data processing. Overall, this versatility makes Scrapy a powerful tool for developers and data analysts alike.