Build vs Buy Data Pipeline: What’s Best for Web Scraping

TL;DR:

The article compares build vs buy data pipeline scenarios, contrasting cheaper off-the-shelf scraping APIs with more flexible custom solutions built in-house or by an outside team. It shows how custom development services combine the benefits of both alternatives, providing full flexibility while allowing clients to skip hiring.

An average business risks $3 million monthly due to pipeline downtime. The systems are often not inherently bad, but they don’t fit a particular use case or new challenges like AI integration. If you’re choosing between build vs buy a data pipeline for web information, this article is for you. We break down the available web scraping solutions and explain how to select one that suits your application and maintenance capabilities.

Scraping API vs Custom Scraper

Scraping APIs offer ready-to-use solutions to collect data from popular online sources. You adjust settings and work within a provider’s infrastructure. A custom scraper, on the other hand, is built from scratch to fit your particular use case. It can seamlessly fit a larger data pipeline where you use the collected information.

Wondering what exactly we mean by data pipelines? Read our explainer.

What Is Scraping API

A web scraping API is a tool for automated data collection from websites and other public sources. It usually functions as a web platform or desktop software with subscription plans or pay-as-you-go options.

With an out-of-the-box scraper, the technical side is pre-built, allowing users to start collecting data with minimal learning curve. This format has both pros and cons.

The Benefits of a Custom Scraper

A custom scraper is built around your use case and business priorities from the start. It takes longer and needs more investment upfront. However, its benefits can yield higher returns. They include:

• Flexibility. You get complete control over the scraping process and can scale it at any moment. That means not only adding more sources, but also doing more with the output.
• More integration options. You can build the data into your product and set up automation beyond a simple data delivery API most platforms offer.

Example: Our client has tried using a scraping service to track changes in the US legal job market. He set it up to notify him about page updates, yet struggled to integrate it into his workflow. DataOx has developed a custom legal recruiting platform fed by 3000 scrapers, reducing workload by 50%.

• Regulation consideration. Most tools follow overall ethical practices, but leave the ultimate responsibility to you. With a custom scraper, you can create it with your state’s requirements in mind.
• Cost-efficiency at scale. If you plan real-time monitoring, paying for each API run will add up quickly. Your own solution pays off over time.
• Security. Full control over the data pipeline is especially important for sensitive industries like finance or healthcare.

If a custom-built web data pipeline fits your use case better, your next step is to decide who is going to build it.

In-House vs Outsourced Scraping

The in-house approach is the most secure, but requires dedicated engineering resources to develop, maintain, and scale the infrastructure. It has the most hidden costs related to hiring and scaling up, and takes the longest.

Outsourcing, on the other hand, produces results faster and reduces operational overhead. Below is a quick guide to choosing the best option for you.

1. Do you need results fast? If yes, outsource.
2. Do you have a tech team? If yes, can you afford to divert its focus? If so, you can build in-house.
3. Can you afford to hire and retain a team? If no, it’s better to outsource.

If your answers point to outsourced scraping, get in touch with the DataOx team for a free consultation.

When Outsourced Scraping Is the Best Option

In-house development often takes longer and is more error-prone. 80% of surveyed data leaders had to rebuild data pipelines after deployment. Hiring an experienced team lowers these risks and helps mitigate some downsides of custom scrapers like prolonged development. It is the best option for businesses that need a tailored scraping solution yet do not specialize in building data pipelines.

Build vs Buy Data Pipeline: Web Scraping Cost Comparison

The final price of a particular scraping solution depends on the number and complexity of sources, schedule, built-in ETL, delivery methods, and more. In addition, the costs go far beyond what’s in the bill. Here’s a comprehensive breakdown.

To sum up, Scraping APIs have a low entry barrier, but offer limited flexibility for complex or large-scale projects. In-house development provides full control and customization, yet can be time-consuming and increasingly expensive. Custom web scraping services can be a middle ground that combines the benefits of the other two options and offers predictable pricing.