The Difference between “Usual” Data Scraping and Big Data Scraping
Below, we’ve described the most common differences between normal data scraping and big data scraping.
When you try to scrape one website many times, you might be blocked from scraping it. Some websites have limitations on the number of requests for a particular time or from a particular location. In that case, you need to use proxy servers—remote computers with different IP addresses. It helps to create the illusion that different users are trying to access the targeted web source. If you’d like more information on using proxies, check out this large topic in our blog.
Complex, cloud-based crawling systems
Depending how many web sources you want to scrape, you may need to use a web crawling system. It helps you to visit all the web sources you need and scrape them for relevant information. All this stuff needs to be managed by special crawling software. It will decide when and which web source should be visited from which location. And the software will set special rules for web scrapers and web parsers—relatively simple software that you can just copy and operate with extracted information.
Cloud-based storage management systems
These systems allow you to manage and store scraped data. Big data needs equally big storage. You can scrape images, texts, or other files—each data type requires its own data storage and data management systems.