Scrapy vs StormCrawler

Struggling to choose between Scrapy and StormCrawler? Both products offer unique advantages, making it a tough decision.

Scrapy is a Development solution with tags like scraping, crawling, parsing, data-extraction.

It boasts features such as Web crawling and scraping framework, Extracts structured data from websites, Built-in support for selecting and extracting data, Async I/O and item pipelines for efficient scraping, Built-in support for common formats like JSON, CSV, XML, Extensible through a plug-in architecture, Wide range of built-in middlewares and extensions, Integrated with Python for data analysis after scraping, Highly customizable through scripts and signals, Support for broad crawling of websites and pros including Fast and efficient scraping, Easy to scale and distribute, Extracts clean, structured data, Mature and well-supported, Integrates well with Python ecosystem, Very customizable and extensible.

On the other hand, StormCrawler is a Development product tagged with crawler, scraper, storm, distributed, scalable.

Its standout features include Distributed web crawling, Fault tolerant, Horizontally scalable, Integrates with other Apache Storm components, Configurable politeness policies, Supports parsing and indexing, APIs for feed injection, and it shines with pros like Highly scalable, Resilient to failures, Easy integration with other data pipelines, Open source with active community.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.