Web Crawling vs Scraping: What’s the difference between crawlers and scrapers?

The terms “web scraping” and “web crawling” are frequently interchanged. After all, aren’t both used for data mining? The truth is that although they are similar, they are not the same.

In this article, we’ll go over the basic distinctions between web crawling and web scraping, and help you decide which one is right for you and your business.

What is web crawling?

Web crawling is essentially the use of an Internet bot – also known as crawlers or spiders – that “crawls” the Internet and gathers pages and data to index or create collections.

Simply put, a crawler visits a website, reads the content on the page, and then follows all the links on that page to crawl even more pages to create entries for search engine indexing.

Resulting in a thorough search for information extraction. Online crawling is performed by well-known search engines such as Google and Bing, and this information is used to index websites.

How does exploration work?

Web crawling uses a spider (or crawling agent) that locates and obtains information from the deepest layers of the World Wide Web by crawling every nook and cranny of the Internet. If we were to explore an e-commerce web page, the procedure would be as follows:

  1. The crawler navigates to the URL you specified, also known as the starting URL: http://example.com.

2. It gathers all the page data and follows all the links it can find in the navigation menu, page body and footer.

3. Product, content and category pages are discovered.

4. All data contained in product pages (price, description, title, etc.), content pages and category pages are collected and indexed or stored in a database.

Thus, web crawlers sift through huge amounts of data and information to find and collect all data from relevant websites for your project.

When to use a web crawler?

More technical industries will most likely benefit from web crawling over scraping. If you want to browse large data sets and explore websites in depth, you will want to use a web crawler. This means you will be able to do what search engines do – scour the web for information and click on every available link and index the data the same way Google does, and collect as much information as possible.

The crawler will also sort the pages to organize the data as desired, in addition to performing other functions to help users find what they are looking for in the database. As you will see later, it is also an essential part of web scraping.

Tools for web crawling


Scrapy is a must among the web crawling technologies available on the market. It is a high performance web crawling and scraping framework commonly used for web crawling. It can be used for data mining, monitoring, and automated testing, among others. Scrapy is pretty easy to use if you’re familiar with Python. It is compatible with Linux, Mac OS X and Windows.


Heritrix is ​​a popular, fast and scalable, free and open source Java web crawler. You can crawl/archive a bunch of websites in minutes. It is also designed to comply with robots.txt exclusion guidelines and robots META tags.

Apache Nutch

Apache Nutch is a fantastic crawler software project that you can use to scale your website. It is particularly known for its use in data mining, and it is a cross-platform solution based on JAVA. It is widely used by data analysts, data scientists, application developers, and web text mining engineers for a variety of applications.

What is Web Scraping?

Web scraping is a technique for extracting specific data from websites and exporting it to a local workstation in XML, Excel, JSON or SQL format. Scripts used to automate this process are called web scrapers which can extract data from any website in a fraction of the time a person would, based on the requirements provided. This automation of tasks is very beneficial for collecting data for machine learning and other purposes.

How does scraping work?

The first step in web scraping is to request the content of a specified URL from the target website. In exchange, the scraper receives the desired data in HTML format.

Then the crawler will parse* the HTML DOM to find the data you specified on your scripts using CSS or XPath selectors.

To note: * HTML parsing is the process of processing HTML code and extracting relevant information such as page title, links, headings, etc.

The last step is to download and save the data in a CSV, JSON or any other database format so that it can be retrieved and used manually or in any other software.

We can break down the web scraping process into four steps:

  1. The robot sends an HTTP request to the server and downloads the HTML DOM of the target URL.

2. Then it will parse the DOM to find the specified elements in the page and ignore the rest of the content.

3. All items are now checked out.

4. The data is added to the specified database.

Of course, scraping a page isn’t exactly the most useful implementation. So we can add an extra step to this process by adding web crawling functionality to the web scraper to find and follow specific links within the page.

This will allow you to scrape an entire product category or catalog within a website using navigation links, for example.

When to use a Web Scraper?

If you want to download the acquired data, web scraping is the way to go, as it is a more targeted approach if you consider scraping rather than crawling.

For example, to determine how to place their new product in the market, a company can take details of laptop products offered on Amazon by scraping data from Amazon. Using scraping proxies, you can modify commands and extract particular information from your target website. After that you can save the results in a useful format (eg JSON, Excel).

In some circumstances, however, web scraping versus web crawling is not a debate. In fact, you might want to use both web crawling and web scraping to achieve a single goal.

By treating them effectively as steps 1 and 2 of your process, you can use a crawler to collect large amounts of data from important websites while using a scraper to extract and retrieve the precise data you have. need from each crawled page.

Tools for Web Scraping

Cheerio and Puppeteer

Cheerio is a powerful tool for analyzing virtually any HTML or XML document implementing a subset of JQuery, designed specifically for the server. It lets you use CSS and XPath selectors to quickly find elements in markup, making it perfect for web scraping with Node.js.

Because it does not render the HTML document or execute the JavaScript files, Cheerio’s performance is extremely fast. However, for this reason, it is not the best choice for scraping dynamic pages.

This is where Puppeteer can shine. By combining Puppeteer’s headless browser manipulation to run JS, click links/buttons, scroll down, etc., with Cheerio’s analytics capabilities, you’ll be able to retrieve any information you want.


Rvest is a library/package (inspired by frameworks like Beautiful Soup) designed to simplify web scraping in R.

The beauty of this library is that not only does it allow you to retrieve specific data from web pages, but it can also create high-quality data visualizations, import into multiple data formats with a simple command, and manipulate them in the data frame.

Scraper API

The Scraper API is a sophisticated solution that uses third-party proxies, machine learning, huge browser farms, and years of statistical data to ensure bot security tactics never stop you.

The web scraping API supports proxy rotation, geo-targeting, and CAPTCHAs, allowing developers to scrape any page with a single API call.

With over 20 million residential IP addresses in 12 countries and software capable of rendering JavaScript and solving CAPTCHAs, you are able to recover huge amounts of data quickly and without fear of being blocked by servers. .

Differences between Web Scraping and Web Crawling

Web Recovery

Web crawling

It is a tool to get specific items or data from web pages

It is a tool for indexing web pages

These types of scripts are called web scrapers.

These types of scripts are called web crawlers, spiders or bots.

It searches for specific elements in a particular page or set of pages

It crawls through every page, looking for information down to the very last line

It can be done on a small or large scale

It is mainly used in large-scale projects

In most cases, a Web Scraper ignores robots.txt

Robots.txt is always respected

Web scrapers primarily use data in retail, marketing, stock research, real estate, and machine learning

Search engines primarily use web crawlers to find new websites or web pages, sort data, and provide users with search results.

All scrapers need a crawler to locate information and a web crawler to scrape information at scale

Crawlers simply require the use of a crawl agent

Using Web Crawling and Scraping for Scalability

Since crawling and scratching include related activities, it’s easy to confuse them. However, web scraping and web crawling have drastic differences and are used for their own purposes.

By now, it should be obvious that web scraping is essential to the success of a business, whether it’s for customer acquisition or revenue development.

The future of web crawling and web scraping also looks advantageous with high scalability and efficient data integration. As the internet becomes the primary source of business intelligence, more publicly available data will need to be mined in order to gain business insights and stay ahead of the competition.

Don’t miss the efficiency of data collection with web crawling and web scraping.

Rosemary S. Bishop