Compare A-Parser vs. Gaffa

A-Parser is an advanced, self-hosted platform designed for high-efficiency web scraping and data gathering tailored for SEO experts, marketers, developers, data engineers, and teams in e-commerce. It features over 110 pre-built parsers that cater to various online resources, including search engines, Google Maps, YouTube, SEO tools, keyword analytics, domain services, and many others. Additionally, users have the flexibility to create custom scrapers using technologies like RegEx, XPath, JavaScript, and TypeScript while automating browser-based data extraction through Chromium and Puppeteer. The software also allows for managing and rotating proxies and supports the execution of both nested and sequential scraping tasks. Operating on Windows and Linux, A-Parser offers compatibility with macOS through Docker, complemented by a web-based user interface and an HTTP/JSON API specifically designed for enterprise-level users. This comprehensive functionality makes A-Parser an invaluable tool for anyone looking to efficiently collect and analyze data from the web.

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.