With over 1 billion websites online today, the web has become the largest data repository ever created. For businesses, all this web data represents a massive opportunity to gain competitive insights.
But extracting and leveraging this data poses some key challenges:
- How do you access and collect relevant data from websites?
- What are the options available for extracting data at scale?
- How do you choose between the different data extraction methods?
The two most common technical solutions for extracting data from websites are web scraping and APIs.
In this comprehensive guide as a web scraping expert with over 10 years of experience, I will compare these two approaches across 7 key factors:
- How They Work
- Solution Availability
- Stability
- Access to Data
- Technical Difficulty
- Cost
- Legal Implications
I will also provide detailed examples of when web scraping or APIs may be better suited for data extraction from popular sites like Amazon, Twitter, and Instagram.
How Web Scraping and APIs Work
First, let‘s deep dive into what web scraping and APIs are and how they work technically:
What is Web Scraping?
Web scraping refers to the automated extraction of data from websites through software programs known as web scrapers, web spiders or web crawlers.
The web scraper browses websites in the same way as a human user would, but instead of visually reading the content, it systematically extracts structured data from the HTML, texts, images and other elements of website pages.
Here is how a typical web scraper works:
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The scraper visits the target webpage by sending an HTTP request.
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The web server returns the HTML content of the page in response.
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The scraper parses through the HTML to extract relevant data into variables.
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The data is structured and exported, usually into formats like CSV, JSON or Excel.
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Web scrapers repeat this cycle at high speeds to extract data from thousands of pages.
7 stages of a typical web scraping process (Image source: AIMultiple)
For example, an e-commerce site could use a web scraper to extract details of products like price, description, images from competitors‘ sites. The scraped data can then be analyzed to make pricing or assortment decisions.
Web scrapers can extract pretty much any data contained in the HTML source code of web pages from content to metadata to scripts. The scope ranges from simple scrapers extracting headlines from news sites to complex scrapers mimicking user actions like login.
What are APIs?
API stands for Application Programming Interface. APIs essentially provide direct access to data from a website‘s database to external applications.
Instead of an application having to scrape the website UI to get data, the API serves data through structured requests and responses.
For example, the Twitter API allows developers to build apps that can post tweets, follow users or favorite posts without having to parse Twitter‘s interface.
Here is how web APIs work:
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Developer registers and gets API credentials like keys or tokens.
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The app sends API requests referencing docs for data needed.
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Requests are authenticated using API keys and rate limits.
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Twitter API returns response with JSON structured data.
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Developer‘s app processes data for usage in the app.
So in summary, APIs provide direct conduit to harvest certain data from a website‘s backend, without needing to mimic a user scraping the frontend website.
Key Differences in How They Work
| Web Scraping | APIs |
|---|---|
| Accesses data from front-end website UI | Gets data via direct access to back-end databases |
| Extracts all publicly available data | Returns only portions of data allowed by the API |
| Simulates human visitor behavior | Structured requests and responses |
| Prone to changes in site layouts | Stable as per developer docs |
| No rate limits except from proxies | Strict rate limits controlled by provider |
This table summarizes some of the main technical differences in how web scraping and APIs function. The key contrast is that web scraping simulates user interactions with the website UI, while APIs provide direct structured access to internal data.
Availability of Web Scraping and API Solutions
Before choosing between web scraping and APIs, the first question is – does the website even offer these options?
Let‘s look at solution availability more closely:
APIs
The prerequisite for using APIs is that the website needs to explicitly provide API access to their data systems.
Many popular social, e-commerce and media sites like Twitter, Amazon, YouTube, Reddit etc. have published their own APIs available for use. There are also aggregated API directories like ProgrammableWeb that catalog thousands of web APIs across diverse categories.
However, smaller websites may not have APIs available. Even larger sites restrict API access to certain types of data. For example, Netflix and StubHub do not provide public APIs.
So API access depends completely on the website provider enabling it. If they don‘t, APIs are not an option.
Web Scraping
The big advantage of web scraping is it can work on any website that has content accessible through a web browser.
Unlike APIs, web scraping does not rely on access provided by the website owner. As long as a site is indexed by search engines like Google, web scrapers can also extract data from it.
The only exception are sites that explicitly employ technical measures to block scraping, like Craigslist, Facebook, Netflix etc. For most normal websites, scraping is perfectly feasible.
In summary, web scraping provides universal coverage to extract data from almost any public website on the internet. API access depends on availability and is more limited.
Stability and Reliability
Stable data extraction with minimal disruption is essential for most businesses reliant on web data. So how do web scraping and APIs compare on stability?
API Stability
APIs generally provide the most stable and reliable method to get web data, for two reasons:
Official Access – APIs provide officially approved access points to data systems. So changes are incremental rather than disruptive.
Provider Support – Issues with APIs can be routed to the provider‘s technical support team for quick resolution.
For example, if Twitter changes it‘s data structure, it will take months to reflect in their API after extensive developer notifications. Emergency fixes are also quickly provided.
Web Scraping Stability
Web scraping however comes with some inherent stability risks:
Fragility – Scrapers are highly prone to breaking with even minor changes to page layouts or class names. Frequent maintenance is required.
Blocking – Many websites actively try to detect and block scrapers with each side constantly adapting. This can lead to scrapers losing access if blocked.
No Support – There is no official channel to resolve scraping issues with the website owner. Troubleshooting problems on your own can be challenging.
Based on my experience across over 100 web scraping projects, APIs provide significantly more stable and seamless data extraction than web scraping. While scrapers can be engineered to be resilient, they inevitably require more maintenance effort.
Access to Website Data
APIs and web scraping also differ in terms of flexibility in accessing different data from a website:
API Data Access
Even if an API is available, it may not expose all of the site‘s data or provide complete access to core systems.
Some limitations are:
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Limited Data – APIs are purpose built for specific use cases and provide access to only select datasets. For example, the Twitter API allows extracting tweets and user profiles but not analytics.
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Partial Data – The granularity of data provided might be limited based on API permissions. The LinkedIn API gives only partial profile data for example.
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Rigid Structure – The data and structure is predefined in the API specification. So flexibility to scrape additional related data is limited.
So while APIs provide authorized access, they intentionally limit what data can be extracted.
Web Scraping Data Access
Web scraping essentially allows extracting any publicly visible data from a website, with a few caveats:
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Can scrape any content visible to users in theory, including text, images, documents, media etc.
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No inherent limits on what pages or data-types can be scraped.
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Restriction is to comply with the site‘s Terms of Service and acceptable use policies.
For instance, LinkedIn profiles contain much more data like connections, groups etc. which can be scraped but not available via their API.
The main advantage of web scraping is flexibility to extract any data exposed publicly on the website, beyond API restrictions.
Technical Difficulty
Both web scraping and APIs require some degree of technical expertise to implement and manage:
API Technical Complexity
Using APIs seem simple in concept, but can pose some technology challenges:
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Developing code to interface with an API requires understanding protocols like REST, SOAP, HTTP etc.
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Correctly using authentication mechanisms like API keys, OAuth, sessions etc. is vital.
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Each API has specific documentation which needs thorough comprehension to implement.
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Managing usage limits, quotas, rate limits requires technical diligence.
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Monitoring and handling errors like HTTP codes, parsing responses adds overhead.
While API docs and sample code help accelerate development, integrations still require specialized programming skills.
Web Scraping Technical Effort
Building custom scrapers also necessitates technical capacity around:
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HTML parsing, DOM manipulation, asynchronous programming in languages like Python or JavaScript.
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Mimicking browser behaviors like AJAX requests, cookies, headers.
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Employing techniques like proxies and browsers to avoid blocks.
However, unlike APIs, there are many SaaS tools and browser extensions available that allow web scraping without needing coding expertise:
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Cloud services like ScraperAPI, Octoparse, ParseHub, Import.io handle the heavy lifting and just need configuration.
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Browser extensions like Web Scraper and Data Miner scrape any page with clicking and UI configuration.
So basic web scrapers can be set up without programming skills, making it more accessible than custom API integration. But advanced scenarios would still need developer involvement.
Cost Comparison
The costs involved in leveraging web scraping and APIs can influence the decision making:
API Cost Considerations
APIs may seem free to use, but there are some pricing considerations:
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Most APIs have free tiers but with tight usage limits and quotas. For example, the Twitter API rate limits to 900 requests per 15 minutes in the free tier.
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Once volumes cross these thresholds, payment plans based on transactions, calls, bandwidth etc. have to be purchased. The costs compound quickly with scale.
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Many APIs like Google Maps are entirely usage based, so expenses rack up linearly with more data. Large enterprises often spend millions per year on commercial API usage.
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For extremely high volumes, some providers like Twitter even require custom contracts exceeding standard pricing.
So while free tiers do exist, commercial API usage gets very expensive with scale.
Web Scraping Cost Dynamics
There are some pricing nuances to keep in mind for web scraping also:
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Open source scrapers are free but require technical skills for use and maintenance.
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SaaS services have monthly subscription plans scaling based on requests, bandwidth etc. Plans from $50 to $1000 per month are common for commercial usage.
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Managed scrapers are custom projects priced based on complexity, frequency and data needs. One-time costs range from $1000 upwards based on effort.
So web scraping tools have very cost-effective options for smaller workloads. But larger scrapers would incur significant custom development costs akin to building from scratch.
In summary, web scraping tools have affordable options at smaller scales while heavy API usage ends up expensive for enterprises. But custom large scrapers are cost intensive too.
Legal and Ethical Considerations
With both web scraping and APIs, there are some legal nuances to consider:
API Legalities
APIs provide explicitly allowed access to websites, so using them is completely legal with some basic compliance:
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Abiding by the API terms, acceptable use policy and rate limits is mandatory.
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Not sharing or reselling API access without permission would be violation.
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Downloading large portions of data through APIs for commercial use may violate licensing.
As long as the developer agreement is followed, APIs provide legal access.
Web Scraping Laws
The legal standing of web scraping is more complex:
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Technically, scraping public website data without circumventing blocks is not illegal in most countries.
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But scraping data and republishing it commercially without permission could lead to copyright violations.
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Ignoring blocks and scraping sites like Facebook and Craigslist despite denial of access is illegal.
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Scraping responsibly within acceptable use policies and robots.txt directives is usually legally compliant.
So the line between legal and illegal scraping often comes down to how data is scraped and used rather than the act itself. But ambiguity exists in certain cases.
Case Studies: Scraping Popular Sites
Now that we have compared web scraping and APIs across key aspects, let‘s see how they stack up for some popular websites:
Scraping Amazon Data
For extracting product data from Amazon, the Product Advertising API is available. However, it has some limitations:
- Need to register as an Amazon Associate for access which has eligibility criteria.
- Restrictive data quotas of max 10 products allowed per query.
- Cannot extract reviews, seller details etc.
For more open and scalable Amazon data, web scraping is the better choice:
- Can extract all details publicly visible on product pages like price, rating, images etc.
- No relationship with Amazon required.
- Can extract thousands of product pages per hour based on need.
- Provides more flexibility like scraping related reviews and seller profiles.
So for Amazon, web scraping provides higher quality data compared to the restrictive Product API.
Scraping Twitter Data
Twitter has a very developer-friendly API with detailed docs for extracting tweets, users and analytics. But some limitations exist:
- Research shows web scraping Twitter is much faster than its API with higher data volumes.
- Twitter API has restrictive rate limits like 900 requests per 15 minutes.
- Need to apply for elevated access levels to increase quotas.
For more heavy duty Twitter mining, web scraping has advantages:
- No rate limits so can extract thousands of tweets/profiles per hour.
- Provides complete access to public Twitter data.
- Full historical tweets can be extracted easily.
So for large scale Twitter data acquisition, web scraping is faster and more efficient vs APIs.
Scraping Instagram Data
Instagram has a Basic Display API. However, it only allows limited profile data and no access to actual posts or media.
Web scraping Instagram can extract:
- All public data like images, captions, comments, profiles etc.
- Visual media which is not available via API.
- Analytics on user activity and engagement.
For Instagram, web scraping provides far more data than the very restrictive official API.
Key Takeaways on Web Scraping vs APIs
Based on this detailed comparison between web scraping and APIs across 7 facets, here are the key takeaways to guide your decisioning:
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Solution availability – Web scraping can extract data from any public website, unlike APIs which have availability constraints.
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Stability – APIs provide more reliable access with official support, while scrapers are more prone to changes.
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Data access – APIs have limits on how much data can be extracted, web scraping allows extracting all public data.
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Technical – Web scraping tools make the process easier compared to coding APIs. But advanced scenarios require developers.
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Costs – For smaller workloads, web scraping tools are very affordable starting at $50/month. Heavy API usage gets expensive.
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Legal – APIs provide authorized access, so are fully compliant if their terms are followed. With web scraping, respecting robots.txt and site policies is key.
Conclusion
To summarize, web scraping and APIs both have their merits based on factors like volume, technical needs, flexibility and costs.
If website APIs are readily available and meet your business requirements, they represent the simpler option. But in many cases, the limitations lead to web scraping being a better fit despite the additional complexity.
The decision depends on the use case specifics – a structured methodology weighting the key variables is essential to determine if web scraping or APIs align better to your goals. Used judiciously, they can both prove to be invaluable techniques for harnessing web data at scale.