Scrapy vs StormCrawler

Professional comparison and analysis to help you choose the right software solution for your needs. Compare features, pricing, pros & cons, and make an informed decision.

Scrapy icon
Scrapy
StormCrawler icon
StormCrawler

Expert Analysis & Comparison

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.

Why Compare Scrapy and StormCrawler?

When evaluating Scrapy versus StormCrawler, both solutions serve different needs within the development ecosystem. This comparison helps determine which solution aligns with your specific requirements and technical approach.

Market Position & Industry Recognition

Scrapy and StormCrawler have established themselves in the development market. Key areas include scraping, crawling, parsing.

Technical Architecture & Implementation

The architectural differences between Scrapy and StormCrawler significantly impact implementation and maintenance approaches. Related technologies include scraping, crawling, parsing, data-extraction.

Integration & Ecosystem

Both solutions integrate with various tools and platforms. Common integration points include scraping, crawling and crawler, scraper.

Decision Framework

Consider your technical requirements, team expertise, and integration needs when choosing between Scrapy and StormCrawler. You might also explore scraping, crawling, parsing for alternative approaches.

Feature Scrapy StormCrawler
Overall Score N/A N/A
Primary Category Development Development
Target Users Developers, QA Engineers QA Teams, Non-technical Users
Deployment Self-hosted, Cloud Cloud-based, SaaS
Learning Curve Moderate to Steep Easy to Moderate

Product Overview

Scrapy
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.

Type: Open Source Test Automation Framework

Founded: 2011

Primary Use: Mobile app testing automation

Supported Platforms: iOS, Android, Windows

StormCrawler
StormCrawler

Description: StormCrawler is an open source web crawler designed to crawl large websites efficiently by scaling horizontally through Apache Storm. It is fault-tolerant and allows integration with other Storm components like machine learning pipelines.

Type: Cloud-based Test Automation Platform

Founded: 2015

Primary Use: Web, mobile, and API testing

Supported Platforms: Web, iOS, Android, API

Key Features Comparison

Scrapy
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
StormCrawler
StormCrawler Features
  • Distributed web crawling
  • Fault tolerant
  • Horizontally scalable
  • Integrates with other Apache Storm components
  • Configurable politeness policies
  • Supports parsing and indexing
  • APIs for feed injection

Pros & Cons Analysis

Scrapy
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
StormCrawler
StormCrawler
Pros
  • Highly scalable
  • Resilient to failures
  • Easy integration with other data pipelines
  • Open source with active community
Cons
  • Complex setup and configuration
  • Requires running Apache Storm cluster
  • No out-of-the-box UI for monitoring
  • Limited documentation and examples

Pricing Comparison

Scrapy
Scrapy
  • Open Source
StormCrawler
StormCrawler
  • Open Source

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