To Build or To Buy? The Keys to a Successful Web Scraping Project

Web Scraping is a key step in data collection and compilation of a dataset. You can either build your own tools or buy tools from web scraping providers, but is it worth building its infrastructure in

By Victor @August, 17 2022

to build or to buy? the keys to a successful web scraping project

 

Introduction

 A recurring question I always get from people starting a new web scraping project is; should I build this myself or should I buy it? My answer is always it depends...

If you have a technical team it is always tempting to dive straight into any technical challenge and try to build solutions, but we should remember that nowadays there is a SAAS solution for pretty much everything so you could always get to market quicker without building. Keep reading to learn everything you need to know about building a web scraping infrastructure in-house and why you might want to take another route.

The Basics of Web Scraping

Web scraping is a way of extracting data sets and different forms of content from a website. Extracting the data will involve using bots to do the data sweep and then compile that data into usable files all in an automated way. Web scraping is different from screen scraping so it's important not to get the two confused. Web scrapers are often used for large-scale projects that process a large amount of data. But before you start your scraping project, there are a few key things you need to consider:

-What is the purpose of your project?

-What kind of data do you need?

-Where will you get the data?

-How will you store the data?

-How will you clean and analyze the data?

Answering these questions before you start your project will help you set realistic expectations and avoid potential pitfalls.

Did you know that web scraping is more than just gathering data? It's a way to automatically take unstructured data and structure it with fewer chances of error. Web scraping or data extraction as many call it can cost quite a bit. This is especially true if you aren't familiar with what you're doing and know all the infrastructure that is required.

If you have a project that requires the collection of large amounts of data from a website, then a cloud-based web scraper might be a useful solution. Many people wonder if they can do it themselves and whilst it's possible, it's often cheaper and more thorough to use a pre-built web scraper or to consult with experts.

 

 

Factors to consider when deciding to build or buy

Before making a decision it is important to plan and educate yourself on the pros and cons of each approach. You can use the below points to start the initial assessment, having the answers to these questions will also help you have intelligent conversations with your internal team or external vendors during the assessment

  • The Scale of the project; Scale and complexity of the project drives so many decisions. If you require millions of records from multiple complex websites vs needing a few hundred rows of data every other month
  • One Off vs Continuous data: A one-off data collection project would not require ongoing investment and R&D whereas a continuous data project requires continuous investment in improving the solution and also maintaining it
  • Do you have the appropriate technical resource to build and maintain; Web scraping is a niche expertise not openly available to most developers. Consideration must be made to understand if the necessary skills are available in-house, also it is important to understand that the budget is available
  • Opportunity cost: Doing any project internally means that there has to be a trade off., something else will not be done as most companies do not have infinite resources

Once you have detailed the answers to all the above factors let's dive into each option to build and buy and go through scenarios where one is better than the other

 

Building a Web scraping solution

The first things to note is that you must have a Data engineering team or skills in-house to support doing this. The learning curve for a newbie to learn this is so high that it will get very expensive and slow down the speed of execution. What else should we consider before looking at this option?

There are a few key things to consider before building a web scraper that might not be too obvious:

- Server costs; web scrapers are compute heavy so factor in an additional budget for this. Except you want to run your scrapers locally on your laptop you will need to buy servers and probably a database

- Proxies costs; It is well known that webmasters are suspicious of the same IP visiting the same website frequently. It is usually classified as malicious activity so webmasters will typically block that IP. Every successful web scraping project will need a large pool of IPs to be rotated. This comes at a price so has to be factored

- Maintenance cost: As the project scales you will need expertise with Devops to manage the servers and proxies. You will also need developers time to fix scrapers when they break (yes they do break frequently)

- Research & Development: Web scraping is one of the fastest moving spaces. Website technologies are constantly changing, websites constantly introduce anti-bot protection. Just because your scraper is working today, this does not guarantee it will work tomorrow. A culture of continuously researching the latest tools, techniques, and methods is an investment that must be considered if you are building in-house.

 

What Exactly Does A Web Scraping Infrastructure Do and How Does It Help You?

Any infrastructure will have a variety of components to it, let's go through the most important ones in relation to web scraping. You'll want to identify where you want to host your scraper. This could be on your dedicated server or it could be on a cloud server.

If it's on a cloud server, you might have to pay a monthly fee for the amount of bandwidth you consume. If you're hosting on your dedicated server, you'll have more control over your data but it will also come with a more expensive bill.

Then, you'll want to determine what programming language you want to use to build your scraper. Some of the most commonly used languages for scraping include Python, R, and PHP.

Python, however, is known for being the programming language of choice for a web scraping data project. You'll also want to decide how you want the data structured. Speaking in general, there are two ways to structure data.

You can use a relational database management system to store data in tables. This is often done if you're storing data for reports or visualizations. This type is also more of an SQL query language.

You can also make use of small pieces of code to complete a web scraping project with this language. Or, you can store data in a non-relational database management system if you want to do things like store large amounts of data or perform calculations

There Is a Big Picture

The big picture here is that there are a lot of steps involved and there is more than one way to do certain things. The entire process will involve deciding on your coding language, inspecting data, and then writing the code you will use to guide the inspection. Then, you will still need to implement the code to follow through with the rest of the project.

If you're not a software engineer, a data analyst with a strong coding background, or if you don't have any programming experience, you might not know where to start. This is the main reason that businesses turn to use a pre-built web scraper as an alternative.

It gives you the same result, if not better because web scraping templates are designed by professionals. And it could cost significantly less and take less time.

 

Top scenarios when you should build?

  • The company has a data engineering team with experience building and maintaining web scraping projects
  • You have sensitive/security requirements which cannot be satisfied by a vendor
  • You have super custom requirements that require long periods of R&D, and cannot be fulfilled by current web scraping tools/services
  • When web scraping is core to your business strategy and the IP needs to be controlled in-house

 

Advantages of Building an in-house web scraping solution

The two main reasons to build a web scraping application are customization and control. Building your own app allows you to customize everything from the back-end logic all the way down to how data is sorted and presented.

Customization: As you are building this for your custom requirements you will have the ability to build this exactly how best it fits your needs. You will know everything about the code and logic. You will know exactly to fix it when stuff breaks, you can also prioritize any features you want to add as you please.

Control: You have full control over how it is managed and maintained and even how the data is captured and transformed. All the servers are under your management and you do not rely on any third party

 

There Are Some Challenges Doing It In-House

Doing your web scraper design in-house will come with its fair share of hurdles. There are the ongoing issues of having to manage proxies and bot access can be tough to get around without the proper experience. Regular maintenance requires updates and constant observance.

This is one of the main issues with developing an infrastructure internally. There are also the potential issues of continuing costs and ensuring the accuracy of your data excavations.

Disadvantages of Building an in-house web scraping solution

The main drawback to building your in-house web scraping solutions are;

  • It takes a long time to ramp up and build and test all the capabilities needed
  • The costs can be hard to predict and often will cost more time and money than expected, compared to a vendor tool that has fixed pricing
  • You have to maintain and pay for more infrastructure, often having to hire devops to manage servers and proxies
  • It can take away focus of resources from your core business and lead to opportunity cost
  • You need to invest time and money in learning about the newest technologies in the field

 

Pros and Cons of Building a Web Scraping Infrastructure In-House 

Building out a web scraping infrastructure in-house is a good way to receive a customized option. This is one of the bigger advantages of doing it yourself. You will essentially have the ability to tailor the design and functionality to your business's needs.

The downfalls might counter the advantages of completing the project on your own though. It can take quite a bit of time and become costly. Also, if you don't have the expertise to see the project from start to finish, there are some key things you might miss.

How much does building a web scraping solution cost?

A typical project scenario of 5 websites of around ~20k rows per month will cost

  • ~$200/month for proxies
  • ~$300/month for proxies
  • ~30-60hrs a month of developer time

Resources

 

Buying a Web scraping solution

While there are many web scraping tools available for purchase, it is important to consider a few key points before making a purchase. First, consider the size and scale of the project. If the project is small, a pre-built web scraper may be the best option. However, if the project is large or complex, it may be necessary to build a custom web scraper. Second, consider the skills of the team. If the team is not experienced in web scraping, it may be necessary to purchase a web scraper that is easier to use. Finally, consider the budget. There are many web scraping tools available at a variety of price points. It is important to consider the features and functionality of the web scraper in relation to the price.

What About Using Pre-built Options?

There are a variety of advantages to web scraping such as the ability to scale extracted data, automatic data delivery, and a flexible way to extract and organize it all. Whilst there are multiple benefits to compiling data sets with this method, it can become even easier and cheaper with a pre-built web scraper. If you use a pre-built option, all the legwork will already be complete.

You will benefit from additional advantages like;

  • Cost-effectiveness
  • Lower maintenance costs
  • Less of a learning curve

The main advantages are that it’s a ready-made product. You will also waste less time and there is no need for coding experience.

Pre-built options also handle different components throughout the scraping process. For example, a pre-built API reduces your chances of blockage throughout the scraping process. It also offers an excellent way to break down data at a faster rate.

 

Top Factors to Consider when Choosing a Web Scraping Tool to buy

Without much experience, web scraping might appear relatively low cost and simple. But in reality, it can often be painful if you make the wrong choices on tools. 

Here are some factors to consider before making a choice:

  • Setup time 
  • Does it require developer assistance? 
  • Price
  • Scalability
  • Handling Anti-Scraping 
  • Customer support
  • Maintenance
  • Local vs Cloud
  • Features

 

Advantages of Buying

  • Speed to Market: With most scraping tools/services you can start getting data almost immediately because they have already built all the infrastructure to get going
  • No extra infrastructure to pay for or maintain. As with any cloud service you are abstracted from managing servers and proxies
  • Customer support; Web scraping is notorious for being fragile, things break alot. With most Web scraping tools/providers they often provide support to deal with all the issues you would normally have to spend time doing yourself
  • Outsourced R&D: Most tools will keep improving their capabilities in-house to ensure their service is keeping up with the ongoing technology challenge
  • Pay only for what you get; With an in-house tool if things go wrong you still have to pay for an in-house team to fix things regardless of how long it takes. When you outsource you will only pay when you are successful with the service e.g some tools only charge you based on successful API requests or no of rows extracted. Typically prices are fixed monthly so you know exactly how much you pay every month

 

Disadvantages of Buying

The biggest disadvantage of buying a web scraping tool is that you lose the control of completely customising the tool to fit your use case

How much does buying a web scraping solution cost?

Buying a pre-built tool could cost from $49- $500 per month

Completely outsourcing to a data provider could start from ~$1000

 

Should You Build or Buy a Web Scraper?

Now that you know a bit more about web scraping, you might know what option is more appropriate for you. If you want the job done the correct way and the first time, you should work with Web Automation.

Consider how much data you need to extract and what programming languages you know. Also, consider your proficiency in those disciplines. If you'd prefer to have your project completed whilst saving your company money and keeping it on budget, work with an expert. Start a free trial with us today. 

 

Conclusion

Web scraping can be a great way to gather data for your business or project. However, it's important to consider a few key points before you begin. Make sure you have a clear goal in mind, and that you understand the risks and limitations of web scraping. Be sure to choose the right tools for the job, and always respect the terms of service of the websites you're scraping. With a little planning and care, web scraping can be a valuable and productive part of your data-gathering process.

WEBAUTOMATION.IO PRE-DEFINED EXTRACTORS

We aim to make the process of extracting web data quick and efficient so you can focus your resources on what's truly important, using the data to achieve your business goals. In our marketplace, you can choose from hundreds of pre-defined extractors (PDEs) for the world's biggest websites. These pre-built data extractors turn almost any website into a spreadsheet or API with just a few clicks. The best part? We build and maintain them for you so the data is always in a structured form.

 

 

Save Costs, Time and Get to market faster

Build your first online custom web data extractor.

Leave a comment:

You should login to leave comments.