The Limitations of Web Scraping with n8n: A Cost-Benefit Analysis

Web scraping is a powerful technique for gathering data from websites, but choosing the right tools for the job can make a significant difference in both efficiency and cost. After exploring web scraping capabilities with n8n in a previous implementation, some important limitations became apparent when attempting to handle pagination and more complex scraping scenarios.

The initial challenge arose when trying to scrape multiple pages of data. With over 4 million items displayed at 30 items per page, the task required navigating through approximately 60 pages. This pagination requirement presented the first hurdle in the n8n workflow.

The Pagination Challenge

To implement pagination in n8n, you need to:

• Access the total number of items (in this case, 4 million)
• Calculate the total pages by dividing by items per page (30)
• Create a loop to iterate through each page

The standard loop functionality in n8n works with multiple items, but in this case, we needed to create a loop based on page numbers. This required using the index run feature to create a loop that iterates from 1 to the total number of pages.

Data Storage Considerations

Another challenge was storing the collected data. Each iteration through a page collects 30 items, which need to be saved somewhere—either in a database or another storage solution. This adds another layer of complexity to the workflow.

The Cost Factor

Perhaps the most significant limitation was the cost associated with using proxies for web scraping at scale:

• The proxy service being used has a limit of about 2000 calls per month
• The scraping service (Scrap Ninja) only allows 75 calls per month on the plan being used
• With 60+ pages to scrape, and the need to regularly update the data, the costs quickly become prohibitive

The Alternative Approach

After evaluating these limitations, it became clear that using n8n for complex web scraping tasks might not be the most cost-effective solution. An alternative approach using JavaScript with libraries like Puppeteer offers several advantages:

• More control over the scraping process
• Lower operational costs
• Only infrastructure costs to consider
• Option to use cheaper IP rotation services if needed

This could be implemented on a VPS with a cron job to run daily updates, making it a more viable long-term solution for extensive scraping needs.

Finding the Right Balance

While n8n remains an excellent tool for many automation tasks and will continue to be used for other aspects of the project (like WhatsApp integrations), this specific web scraping module might be better handled with a more specialized approach.

When evaluating tools for web scraping, it’s important to consider not just the ease of implementation but also the long-term costs and scalability. Sometimes writing custom code, despite the initial development investment, can lead to more sustainable solutions for data-intensive tasks.