"What is the most commonly used crawling SaaS?"
I'm sorry, but that question doesn't have a clear answer.
You've probably read about ten comparison articles. Articles where Octoparse is ranked first, articles where Apify is ranked first, articles where a tool you've never heard of is ranked first.
Since the rankings differ in each list, the more you read, the further you get from a decision.
The reason is simple. In the crawling SaaS market, there are places that sell cars and places that sell articles mixed together, and everyone lines them up in a row and ranks them.
The problem is not "which tool is ranked first." It's "who is driving."
3-line Summary (TL;DR)
- Data crawling SaaS is divided into three types: no-code tool type, developer API type, infrastructure type, and managed service type, and comparing rankings is not valid when the types are different.
- The criterion for choosing is not the brand, but "who fixes it when the collection stops" — if it's the user, it's the tool type; if it's the development team, it's the infrastructure type; if it's the company, it's the managed service type.
- The cost-effectiveness should be judged not by monthly fees, but by the total cost of ownership (TCO) for one year, including maintenance, blocking response, and data gaps.
Table of Contents
- What is Data Crawling SaaS
- The Real Reason Why Ranking Tables Differ Every Time
- Cars vs. Articles: The Reality of Three Types
- Comparison Table of 9 Types
- Which Side Is Our Company On? Self-Diagnosis with 5 Questions
- 3 Steps to Decide Today
- Frequently Asked Questions
- Conclusion
What is Data Crawling SaaS
Data crawling SaaS is a cloud-based service that automatically collects information from websites and provides it in tabular form. Competitive price monitoring, review analysis, market research, AI training data acquisition — most use cases start here.
And most teams make the same mistake here.
"It's a SaaS, so once we subscribe, the data will come."
It takes a month to realize you need a developer after subscribing. Another month to realize the rules you made are broken because the site changed. This is the most common adoption failure pattern seen in supporting over 500 companies.
This is not about choosing the wrong tool. It's about choosing the wrong type.
The Real Reason Why Ranking Tables Differ Every Time
The question "most commonly used" implies a hidden assumption. That everyone uses the same thing.
Reality is different.
- Marketers transferring today's screen data to Excel,
- Development teams collecting millions of data records,
- Receiving data every morning without developers,
They all use the word "crawling," but they are buying completely different products.
That's why ranking tables only reflect the situation of the writer. A non-developer's article ranks the no-code tool first, while a developer's article ranks the infrastructure type first.
There is no "most commonly used SaaS." There is only "the type most commonly used in my situation."
Cars vs. Articles: The Reality of Three Types
1. No-Code Tool Type — Lending a car, but I drive
Octoparse, ParseHub, Browse AI, Listly. This method involves creating collection rules by clicking. It's quick and inexpensive to start. However, both rule creation and repair when the site changes are entirely the user's responsibility.
2. Developer API·Infrastructure Type — Providing a high-performance engine, but our team assembles it
Apify, Bright Data, ScrapingBee. They provide proxies, execution environments, and bypassing blocks, and the crawler is built by the development team. The freedom and scalability are top-notch. However, someone to code and maintain is essential.
3. Managed Service Type — A car with a driver
Managed collection service means a subscription service that operates the collection task itself instead of lending the tool. The company is responsible for crawler development, block response, maintenance when the site changes, collection monitoring, and the company only receives the result data. HashScraper is an example of this type.
The question that distinguishes the three types is one.
Who fixes it when the collection stops on a Monday morning?
Comparison Table of 9 Types
| Service | Type | Target Users | Maintenance Entity | Pricing Structure | Block Response | Korean Support |
|---|---|---|---|---|---|---|
| Octoparse | No-Code Tool | Non-developers to semi-developers | User | Free + Subscription (based on official website) | Template·IP rotation provided | Partial |
| ParseHub | No-Code Tool | Non-developers | User | Free + Subscription | Limited | Not supported |
| Browse AI | No-Code Tool | Non-developers | User (robot retraining) | Free + Subscription | Basic provided | Not supported |
| Listly | No-Code Tool (extension program) | Non-developers | User | Free + Subscription | Limited | Domestic Service |
| Apify | Developer API·Infrastructure | Developers | User (code) | Usage-based billing | Proxy·Browser provided | Not supported |
| Bright Data | Developer API·Infrastructure | Developers·Data teams | User (code) | Usage-based billing | Large-scale proxy infrastructure | Not supported |
| ScrapingBee | Developer API | Developers | User (code) | API call volume billing | Headless browser·Proxy | Not supported |
| DataHunt* | Data Construction Service | Companies (AI·Data teams) | Company | Project·Contract-based | Company responsible | Domestic Service |
| HashScraper | Managed Collection Service | Companies (including non-developmental departments) | Company (free of charge) | Monthly subscription (including development·maintenance) | 195 countries proxy·AI CAPTCHA response | Domestic Service |
* DataHunt is based on past public data as the official website is not accessible as of August 2026 — please verify the operational status directly when considering adoption. Since detailed fees and specs of each service change frequently, it is best to check based on the official website.
The only column you need to look at in the table is Maintenance Entity. The other columns are just the results of that decision.
Which Side Is Our Company On? Self-Diagnosis with 5 Questions
Check it out. These five questions are faster than reading ten ranking tables.
- [ ] When the collection rules break, is there someone in-house who can fix them?
- [ ] Is the collection one-time or repeated daily/weekly?
- [ ] Does the target include logins, dynamic pages, and strong block large sites?
- [ ] If the collection stops for a day, does it create a gap in work (reporting, price response, analysis)?
- [ ] Besides the tool fees, have you calculated the time of the person creating and fixing the rules as a cost?
If the answer to the first question is "no" and the answer to repeated collection is "yes" — no-code tools and infrastructure types are already out of the running. What remains is the managed service type.
Conversely, if it's one-time/low volume and there is someone to fix it, the managed service is excessive. A no-code tool is the right choice.
3 Steps to Decide Today
Step 1. Determine the operator — Answering question 1 in the self-diagnosis determines the type. If it's self, it's the tool type; if it's the development team, it's the infrastructure type; if there isn't, it's the managed service type.
Step 2. Verify by difficulty and scale — For large sites with strong blocks like e-commerce and social media, daily repetition, and over tens of thousands of records, the cost limit of the tool type (human time) quickly increases. Managed services like HashScraper handle this range with over 5,000 domestic site collection experience and 99.7% data accuracy.
Step 3. Compare by total cost of ownership for one year — It's not about monthly fees but the sum of "fees + my time + maintenance + data gap in case of failure." Based on the managed service standard, there are cases of 68% cost savings compared to individual outsourcing annually. The calculation framework is summarized in Comparing Subscription-Based Crawling vs. Individual Billing Reveals the Answer in Terms of Total Cost of Ownership (TCO) for One Year.
Today's task is not to sign up for a tool. It's answering one question from step 1.
Frequently Asked Questions
Q. So, what is the most commonly used data crawling SaaS by companies?
A. The answer varies by type. Global no-code self-collection tools like Octoparse and Browse AI are widely used, while developer-based large-scale collection tools like Apify and Bright Data are popular. In Korea, Listly is used for small-scale self-extraction, and HashScraper is used as a managed service for companies without development resources, with over 500 companies currently using it. There is no "overall first place" as the question itself is not valid.
Q. Shouldn't I start with a free no-code tool?
A. It's a good start. It's sufficient for occasional and small-scale collection from structured sites. However, if you encounter limitations in repeated collection and strong block sites, it's recommended to have an exit plan of "switching types when blocked."
Q. What is the most cost-effective tool?
A. It depends on the scale. For small-scale and one-time collections, no-code tools are efficient; for companies with development resources and large-scale collections, infrastructure types are efficient; for continuous collection without development resources, managed services are efficient. The judgment criterion is the total cost of ownership (TCO) for one year, not monthly fees.
Q. What sets HashScraper apart from other SaaS?
A. It doesn't provide just a tool but operates the collection task itself. Monthly subscription includes crawler development, site change response, block bypass (195 countries proxy), and collection monitoring, and companies receive only the data in the format they want, such as Excel, API, or DB. It has had no legal issues related to collection in 8 years.
Conclusion
Choosing a crawling SaaS is more like hiring than shopping for a tool. It's about selecting the person to operate the collection.
- If that person is me → No-code tool (Octoparse, Browse AI, Listly, etc.)
- If that person is our development team → API·Infrastructure type (Apify, Bright Data, ScrapingBee, etc.)
- If that person doesn't exist → Managed service (HashScraper, etc.)
The checklist for verifying companies is in Web Scraping Service Selection Guide — 7 Things to Check Before Outsourcing Data Collection, and the complete landscape of collection methods is summarized in Comparing Four Methods from Manual Copying to Data Collection Services.
Don't choose a tool. Choose the operator.
Start Now
If you let us know the site and items you want to collect, we can diagnose for free whether it's within the scope of a no-code tool or requires a managed service. New sign-ups receive 50,000 credits and can first check the collection quality with public bots.
