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How Cloud Web Scraping Can Pay off its Cost in 2024

The dilemma of business teams for web scraping is similar to many other technical decisions: should you pay for a cloud service or build your web scraping in house? You hear that there are free solutions, but unsure if it is worth building a technical capacity for that.

You also see many vendors you can outsource the effort to, but not sure which aspects of their service will bring you the most benefit. In this guide, we will explain how in-house and cloud-based web scraping works, how much they cost, their top benefits and challenges. At the end, we will also share tips on which one to use depending on your business needs.

Top 8 cloud web scraping tools

VendorsPricing/moTrialPAYGType
Bright Data$5007-dayNo-code
Smartproxy$503K free requestsNo-code
Oxylabs$497-dayAPI
Nimble$6007-dayAPI
Zyte$100$5 free for a monthAPI
Diffbot$29914-dayAPI
Octoparse$8914-dayNo-code
Scraper API$1497-dayAPI

In-house Web Scraping

How does it work?

You may often see in-house web scraping being referred as “free web scraping”. It is partially true because there are free or open source tools such as browser extensions that you can scrape the web without paying a dime. These resources will scrape the web page that you are at and download the scraped data on your local computer and most of the time will need some cleaning to be processed for your needs. There is also a plethora of online resources that can enable someone with limited coding knowledge to pull thousands of queries from Reddit or top ten URLs of any search term on Google. Is it free and that easy to scrape the web in a way that it meets your business needs? That depends on the expertise on programming and web protocols of your technical resources.

How much does it cost?

It is difficult to put a price tag on in-house web scraping without knowing your exact business need, but let’s try to estimate. A freelance developer will likely cost you $15-$120 per hour depending on the level of experience you need. For a one-time need, that would take a couple of hours. Not too bad. However, if your web scraping need will scale over time, you will need a complete infrastructure that scrapes the sources periodically, processes the data in a presentable way and stores in your database. It is dependent on many other factors, but a very high level estimation for such an automated infrastructure may require multiple weeks to months for technical development. Even if built, you will likely need a recurring cost of technical maintenance since the content you are scraping is dynamic, such as changes in the website structure or data points you need.

Top benefits:

Top benefits of this solution are really dependent on your business need, which we will give examples of.

  • Pay less in the long run: This may be the case if your web scraping need is too small or too big. If your web scraping need is one-time only and very small in scale, you can explore free resources to assess its benefit for your business. On the opposite end, if your business is quite dependent on web scraping, then it may worth investing in technical infrastructure to do it in-house. For example, a financial investment firm may take million US$ decisions based on the signals coming from scraped web data. If the stakes are this high, investing in the technical development may worth it. If you are a marketing agency that needs web scraping as a supporting tool to your analysis rather than a core part of your business, then investing in the technical resources may not pay out in the long run.
  • Control your data pipeline: Like any other in-house development, in-house web scraping will give you freedom to modify the data you collect, especially if your projects are managed with agile methodology. Communicating a new request to an external provider often takes time and if there is any miscommunication, the effort needs to be repeated.

Top challenges:

Web scraping has many challenges, which will translate into more expertise and hours of technical expertise you need to build. We will briefly mention what each of them here:

  • Website alterations requires scraping code to be changed once the scraped website changes its design
  • Honeypots are traps for web crawlers to go into infinite loops
  • IP Blockers disable web crawling from the same location and source if attempted multiple times
  • CAPTCHA blockers detect and block crawlers if they don’t display the behaviors of human traffic
  • Robot.txt files limit the content that can be scraped from the website

To explore how to tackle web scraping challenges, read our in-depth guide on web scraping best practices.

Cloud web scraping:

How does it work?

Cloud web scraping performs the data collection on the cloud, which:

  • Is more powerful and scalable. Namely, if your web scraping need increases from a hundred page to a thousands, cloud web scraping will handle it easier than in-house and will minimize the time spent on the scraping effort.
  • Saves the data on cloud rather than your local machine.

How much does it cost?

The cost of cloud web scraping varies from platform the platform, mostly based on the amount of data you need or the number of hours per day you can use, which translates to a certain amount of data you can scrape. Based on our detailed list of solutions, we see providers that offer pay-as-you-go packages starting as low as $5 to standard monthly packages starting around US$200-350. Many solutions also offer free trials and sample data sets. Feel free to check our list to see what features different providers offer.

Top benefits:

Scale up whenever you need to

The most prominent benefit of cloud web scraping is the scalability of cloud computing. If you run any in-premise solutions, you may have experienced that your servers may not be able to support your increasing workload or data processing. Depending on how many requests a website allows at a time or how much content it has, your web scraping can take hours or even days and slow down other programs you run in parallel. If you already have a scalable cloud computing infrastructure, this may not be a unique advantage for your business, but if not, it is crucial for your other technical operations to not get interrupted.

Store and process your data on cloud

The quantity of the scraped data can be quite large if you scrape thousands of pages at a time. Moreover, the data often comes in formats that need a significant amount of processing since you need to find a specific word or pattern from the text of an entire web page. If you do your web scraping in-house, you will need to store and process that data on your local machines as well. Cloud web scraping services store the data on cloud to save you from additional data storage costs. Depending on your needs and technical resources in house, they also apply data processing on cloud to provide you the scraped data in the format you specified. If you want to understand whether the amount of the data you scrape will be manageable or not, you can either run a mockup in your company or get a free trial from a cloud web scraper to make a decision.

Bright Data is a cloud web scraper solution that offers fast and scalable web data collection. One of their clients in business consultancy faced the challenge of not being able to cope with an increasing amount of web scraping needs with their technical infrastructure and started working with Bright Data to scale their analytics service. Read more about the business case here.

Source: Bright Data

Top challenges:

  • Scaling cost: Cloud web scraping services offer flexible prices, which may allow you to run a small pilot or find an optimal recurring cost that is cheaper than in-house development. However, the cost will increase parallel to the amount of data you need. If web scraping becomes a core part of your business, it is worth assessing the long-term cost of cloud services and in-house development.
  • Strict access rules: Even if you work with a cloud web scraping service, some websites will have terms that bans their content altogether. This will be a challenge for in-house web scraping as well, and should not be a reason to switch to a cloud service. It is worth consulting with your provider in advance whether the websites you need data being scraped will have such barriers before committing to the provider.

Recommendation to business leaders

So which one should you use? Building a tech team in-house or using a cloud-based web scraping service? If web scraping is a core part of your business and you predict an intensive and continuous amount of web data need, building in-house technology team may pay off in the long term. If web scraping is one of the tools you use or you are not even sure if you’ll leverage web scraping in the long run, you can start with a cloud web scraping by using a free dataset, a trial period or a demo to see if there is a significant business benefit for starting off with one of the cloud web scraper services.

Further Reading:

To explore web scraping use cases for different industries, its benefits, and challenges, read our articles:

For guidance to choose the right tool check out our list of cloud consulting services. If you believe that your business may benefit from a web scraping solution, check our list of web crawlers to find the best vendor for you.

For guidance to choose the right tool, reach out to us:

Find the Right Vendors

This article was drafted by former AIMultiple industry analyst Bengüsu Özcan.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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