Make.com (formerly Integromat) is a popular no-code automation platform that lets you connect apps and build workflows visually. Its HTTP module and integrations make it possible to pull data from websites without writing code. But for serious web scraping at scale, Make.com has real limitations that push developers toward dedicated scraping APIs.
This guide compares make.com web scraping against SearchHive's purpose-built APIs across pricing, features, reliability, and developer experience. If you're evaluating whether Make.com can handle your data extraction needs, or looking for a better alternative, this comparison covers everything you need to know.
Key Takeaways
- Make.com charges by operations, not by data volume -- a single scraping scenario can burn through your monthly allocation fast
- SearchHive charges per credit ($0.0001/credit), giving you predictable costs that scale linearly with usage
- Make.com has no built-in JavaScript rendering -- dynamic sites require workarounds or external services
- SearchHive handles JS rendering, CAPTCHAs, and proxy rotation out of the box via ScrapeForge
- Make.com's Free plan gives 1,000 operations/month; SearchHive's Free tier gives 500 credits with full API access
- For production scraping workloads, SearchHive is significantly cheaper and more reliable
Comparison Table
| Feature | Make.com | SearchHive |
|---|---|---|
| Pricing model | Per-operation credits | Per-credit ($0.0001 each) |
| Free tier | 1,000 ops/month | 500 credits/month |
| Lowest paid plan | $10.59/mo (10K ops) | $9/mo (5K credits) |
| Best value plan | Teams $34.27/mo (10K ops + team) | Builder $49/mo (100K credits) |
| JavaScript rendering | No (requires external tools) | Yes (ScrapeForge built-in) |
| Proxy rotation | No (manual setup) | Yes (automatic) |
| CAPTCHA handling | No | Yes (automatic) |
| Structured extraction | Manual free JSON formatter parsing | Built-in parsing + DeepDive |
| Rate limiting | Scenario execution limits | High rate limits on paid plans |
| API access | REST via HTTP module | Native REST + Python SDK |
| Data formats | JSON (manual mapping) | JSON, Markdown, cleaned HTML |
| Geotargeting | No | Yes (country-level proxy selection) |
| Bulk scraping | Limited (sequential scenarios) | Yes (batch support) |
| Support | Community + docs | Priority support on paid plans |
Feature-by-Feature Breakdown
Scraping Capabilities
Make.com's HTTP module lets you make GET and POST requests to any URL, but that's where its scraping capabilities end. You get the raw HTML response and must parse it yourself using Make.com's built-in text functions or JSON parse tools. There's no CSS selector engine, no XPath support, and no DOM parsing.
For JavaScript-rendered pages, Make.com is essentially useless on its own. You need to chain in a headless browser service like Puppeteer or a rendering proxy, which adds complexity and cost to every scenario.
SearchHive's ScrapeForge endpoint handles all of this automatically. Send a URL, get structured data back. It renders JavaScript, handles CAPTCHAs, rotates proxies, and returns clean JSON or Markdown. No scenario building, no external service dependencies.
Pricing Deep Dive
Make.com's pricing is opaque when it comes to scraping. Each HTTP request in a scenario costs operations. A simple scraping workflow might look like:
- HTTP request to fetch a page (1 operation)
- Iterator to parse results (1 operation per item)
- HTTP request for each detail page (1 operation per item)
A single scenario that scrapes 50 product pages consumes 51+ operations. On the Free plan (1,000 ops/month), you can run that scenario roughly 19 times before hitting your limit.
On SearchHive, scraping 50 pages costs 50 credits ($0.005). The Free tier (500 credits) handles that 10 times over. The Builder plan at $49/mo gives you 100,000 credits -- enough for 100,000 page scrapes at effectively $0.00049 per page.
Automation vs. Purpose-Built
Make.com excels at connecting APIs: "when this happens, do that." For orchestrating workflows between Slack, Google Sheets, and a CRM, it's solid. But web scraping is a fundamentally different problem that requires handling HTML parsing, dynamic content, anti-bot measures, and data normalization.
SearchHive is built specifically for web data extraction. Every endpoint is optimized for that use case -- SwiftSearch for search result scraping, ScrapeForge for page extraction, and DeepDive for AI-powered content analysis.
Pricing Comparison in Practice
Scenario: Scrape 10,000 product pages per month
| Solution | Monthly Cost | Notes |
|---|---|---|
| Make.com Free | $0 | Only covers ~200 pages (1K ops) |
| Make.com Core | $10.59 | Only 10K ops -- still not enough |
| Make.com Teams | $34.27 | 10K ops -- need multiple plans |
| SearchHive Starter | $9 | 5K credits -- covers 5,000 pages |
| SearchHive Builder | $49 | 100K credits -- covers all 10K pages 10x over |
For any meaningful scraping volume, SearchHive delivers significantly more value per dollar.
Code Examples
Make.com HTTP Module (JSON configuration)
Make.com uses a visual builder, but here's what the equivalent HTTP request configuration looks like:
Module: HTTP > Make a Request
URL: https://example.com/products
Method: GET
Headers: User-Agent: Mozilla/5.0
Parse Response: Yes
You'd then need a separate Iterator module and Text Aggregator to extract data from the HTML response. This is tedious, fragile, and breaks when the page structure changes.
SearchHive: Scrape a Page in 3 Lines
import requests
API_KEY = "your_searchhive_api_key"
url = "https://example.com/products"
response = requests.get(
"https://api.searchhive.dev/v1/scrapeforge",
headers={"Authorization": f"Bearer {API_KEY}"},
params={"url": url, "format": "json"}
)
data = response.json()
print(data["content"][:500])
SearchHive: Batch Scrape with Geotargeting
import requests
API_KEY = "your_searchhive_api_key"
urls = [
"https://example.com/products/1",
"https://example.com/products/2",
"https://example.com/products/3",
]
results = []
for url in urls:
response = requests.get(
"https://api.searchhive.dev/v1/scrapeforge",
headers={"Authorization": f"Bearer {API_KEY}"},
params={"url": url, "format": "markdown", "country": "us"}
)
results.append(response.json())
# Process results
for r in results:
print(f"Title: {r['title']}")
print(f"Content length: {len(r['content'])} chars")
SearchHive: Extract Structured Data with DeepDive
import requests
API_KEY = "your_searchhive_api_key"
response = requests.post(
"https://api.searchhive.dev/v1/deepdive",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
},
json={
"url": "https://example.com/product-page",
"prompt": "Extract product name, price, rating, and availability"
}
)
data = response.json()
print(data)
Verdict
SearchHive wins for web scraping. Make.com is a competent automation platform, but web scraping is not its strength. You pay for operations that get consumed quickly by HTTP requests, you get no built-in rendering or anti-bot handling, and parsing raw HTML in a visual builder is painful.
SearchHive gives you a purpose-built scraping API with JavaScript rendering, proxy rotation, CAPTCHA handling, and structured output -- at a fraction of the per-request cost. The free tier (500 credits) is enough to evaluate thoroughly, and the Builder plan at $49/mo covers workloads that would cost hundreds on Make.com.
If you're already using Make.com for workflow automation, keep it for that. But for the data extraction layer, SearchHive's ScrapeForge API is the better, cheaper, more reliable choice.
Get started with 500 free credits at searchhive.dev -- no credit card required. Full API access, all endpoints, ready to scrape in under 5 minutes.
See also: /compare/firecrawl, /compare/scrapingbee, /blog/searchhive-vs-serpapi