Skip to content

What‘s the Difference Between Web Scraping and Crawling?

Web scraping and crawling are two techniques used to extract data from websites. While they share some similarities, there are important differences between the scope and approach of each one. This article will examine web scraping vs crawling and how the two techniques complement each other.

Defining Web Scraping and Crawling

Web scraping refers to the extraction of specific data from websites. The scope is narrow and targeted. For example, a web scraper may be configured to scrape product titles and prices from an e-commerce website. Scrapers are focused on capturing defined data from specified sites.

Web crawling involves a broader, more exploratory indexing of website content. Crawlers explore websites more widely, discovering pages and links to scrape. The focus is on exploring and finding relevant content to extract. Search engines like Google use web crawlers to index websites and discover pages.

Key Differences Between Web Scraping and Crawling

While scraping and crawling both involve extracting data from websites, their approach and scope differ:

  • Scraping targets specific data – Scrapers are configured for particular data types, like product information. The extraction is narrowed to key data points.

  • Crawling is more exploratory – Crawlers explore websites more widely, finding new pages and content to scrape. Their focus is discovery of content.

  • Scraping extracts from specified sites – Scrapers gather data from defined sites and pages provided. Crawlers can discover and extract data from many unknown sites.

  • Crawling focuses on discovery – The emphasis is exploring and finding new content to scrape vs just extracting defined data points.

So in summary, web scraping focuses on extracting specific data from known sites while web crawling incorporates scraping as part of a broader discovery and exploration of website content.

Relationship Between Scraping and Crawling

While they have different approaches, web scraping and crawling very much complement one another:

  • Most web scraping tools utilize some crawling techniques. For example, an e-commerce scraper may crawl category pages to find products before scraping each item.

  • Web crawlers scrape content as part of their exploratory indexing. Search engine crawlers scrape page titles, text and metadata as they discover new URLs.

So scraping supports targeted data extraction while crawling powers wider discovery of pages and links to scrape. Many scraping projects leverage both techniques in combination.

Web Scraping vs Crawling Examples

Some examples help illustrate the different applications of web scraping and crawling:

  • Search engines – Search engine crawlers like Googlebot continuously crawl across the web to discover new sites and content. As pages are found, key data like text and metadata is scraped and indexed for searching.

  • Social media monitoring – Scraping would extract defined social data like post text and shares. Crawling helps discover new posts and comment threads to scrape.

  • E-commerce sites -Crawling finds product category and subcategory pages. Scraping then extracts details like product titles, descriptions, pricing for each item.

  • News aggregation – A crawler finds new news articles and pages to scrape while scraping extracts article headlines, text, images and data.

So in each case, crawling supports discovery of content while scraping focuses on extracting key details from each item. The two techniques work together to gather both broad and specific website data.


In summary, while web scraping and crawling share some common functionality of extracting website data, their scope and focus differ:

  • Web scraping provides targeted extraction of defined data points from specified sites.

  • Web crawling enables a broader discovery-driven exploration across the web to find pages and content to scrape.

Scraping and crawling work together – scraping to capture key data from pages and crawling to identify new pages with content to extract. Both techniques are powerful engines for data harvesting from the internet.

Join the conversation

Your email address will not be published. Required fields are marked *