ScrapeStorm vs Scrapy

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

ScrapeStorm is a Ai Tools & Services solution with tags like web-scraping, data-extraction, automation.

It boasts features such as Visual web scraping interface, Point and click site mapping, Extracts data into CSV/Excel, Built-in proxies and captcha solving, Web automation workflows, Cloud-based and self-hosted options, Browser extension for scraping data on-the-fly, APIs for developers, Integrates with Zapier and Integromat and pros including No coding required, Intuitive visual interface, Powerful automation capabilities, Cloud version has large proxy network, Good for beginners and non-technical users.

On the other hand, Scrapy is a Development product tagged with scraping, crawling, parsing, data-extraction.

Its standout features include 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 it shines with pros like 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.

Feature	ScrapeStorm	Scrapy
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Development

Product Overview

ScrapeStorm

Description: ScrapeStorm is a web scraping tool that allows users to easily extract data from websites without coding. It has a graphical interface to visually map sites and extract data into CSV/Excel. Useful for marketing, research, data entry automation.

Scrapy

Description: Scrapy is an open-source web crawling framework used for scraping, parsing, and storing data from websites. It is written in Python and allows users to extract data quickly and efficiently, handling tasks like crawling, data extraction, and more automatically.

Key Features Comparison

ScrapeStorm Features

• Visual web scraping interface
• Point and click site mapping
• Extracts data into CSV/Excel
• Built-in proxies and captcha solving
• Web automation workflows
• Cloud-based and self-hosted options
• Browser extension for scraping data on-the-fly
• APIs for developers
• Integrates with Zapier and Integromat

Scrapy Features

• 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

Pros & Cons Analysis

ScrapeStorm

Pros

• No coding required
• Intuitive visual interface
• Powerful automation capabilities
• Cloud version has large proxy network
• Good for beginners and non-technical users

Cons

• Limited to browser rendering
• Not as customizable as coding web scrapers
• Cloud version has limited requests
• Steep learning curve for advanced features

Scrapy

Pros

• 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

Cons

• Steep learning curve
• Configuration can be complex
• No GUI or visual interface
• Requires proficiency in Python
• Not ideal for simple one-off scraping tasks

Pricing Comparison

ScrapeStorm

• Free
• Freemium
• Subscription-Based

Scrapy

• Open Source