There are many comparison articles on domestic data collection services.
The problem is that most of them are based on outdated information.
After reading ten comparison articles and narrowing down the candidates, one of the websites does not open.
When I inquired with another place, the response was, "We do not provide such a service."
Your time disappears like that. This article redraws the map as of August 2026.
There are two things to do before comparing. Confirming existence and confirming the industry.
Summary in 3 Lines (TL;DR)
- Listly, Datahunt, CODEF, and HashScraper, often mentioned together as the "Big 4 Data Collection Companies" in Korea, offer services that solve different problems — small-scale self-extraction / AI learning data construction / authentication-based institutional data connection / managed web collection.
- As of August 2026, two things have been updated. Datahunt's official website does not open (essential to check operational status before considering adoption), and CODEF provides an authentication-based data 'connection' service separate from web crawling.
- Therefore, the question should not be "Which one is better," but rather "On which map is my data located?" The 5 self-diagnostic questions in this article provide the answer.
Table of Contents
- The Premise of This Comparison Must Be Updated in 2026
- Not All Four Are on the Same Ground: Accurate Definitions Line by Line
- Comparison Table of the Big 4
- Where Is Our Company's Data Located? 5 Self-Diagnostic Questions
- Choosing with the Updated Map in 4 Steps
- Frequently Asked Questions
- Conclusion
The Premise of This Comparison Must Be Updated in 2026
"Listly vs. Datahunt vs. CODEF vs. HashScraper."
This matchup is still circulating when searched. However, there are two errors in this matchup now.
First, as of August 2026, Datahunt's official website (thedatahunt.com) does not open. Although the company has been mentioned as a representative in the area of AI learning data construction and labeling, if you are considering adoption now, checking the operational status should be the first step. The description of Datahunt in this article is based on past publicly available information.
Second, CODEF was not originally a web crawling company. It is a service that connects financial and public institution data standardized through user authentication-based methods like public key certificates to a single API. This is a separate field from scraping web data in terms of data source, technology, and legal structure.
The reason why comparison articles that line up the four companies always produce different winners is because they were never in the same competition to begin with.
Because they were not in the same game from the start, the rankings only reflect the circumstances of the writer.
Not All Four Are on the Same Ground: Accurate Definitions Line by Line
When the map is redrawn, this is how it looks. The four are on different continents.
Listly is a browser extension tool that extracts lists and tables visible on the screen into Excel with a few clicks, a no-code data extraction tool in Korea. From installation to the first extraction, it is the fastest among the four services.
Datahunt is a Korean data construction company that performs the collection, processing, and labeling of AI learning data on a project basis. Their strength lies in high-quality datasets with human curation — however, as mentioned earlier, it is essential to check the operational status before proceeding.
CODEF is a service that connects financial and public institution data using standardized APIs based on user authentication methods like public key certificates. It is about "connecting" data received from institutions, not "collecting" publicly available web data.
HashScraper is a Korean managed web data collection service that handles everything from crawler development to block handling and site change maintenance, providing companies with only the resulting data. It targets companies that need to receive web public data continuously and in large quantities.
Under the same "data collection" banner, the products they sell are all different.
Comparison Table of the Big 4
| Category | Listly | Datahunt* | CODEF | HashScraper |
|---|---|---|---|---|
| Service Method | Browser extension tool (self-extraction) | Project-based data construction | Authentication-based data connection API | Managed collection subscription |
| Main Data Area | Visible tables/lists on the screen | AI learning data (collection, processing, labeling) | Financial/public institution structured data (personal authentication required) | Web public data (e-commerce, reviews, news, announcements, etc.) |
| Target Users | Individuals/non-developers | Companies with AI/data departments | Companies with development teams (API integration) | Companies (including non-development departments) |
| Maintenance Entity | User | Company (within the project scope) | CODEF for API, user for integration code | Company (included in subscription) |
| Pricing Structure | Free + subscription (based on official website) | Project/contract-based | Based on API usage (based on official website) | Monthly subscription (includes development/maintenance) |
| Scalability | Focus on small-scale/manual execution | Depends on project scale | Within the provided API scope | Expansion of target sites/items/frequency |
* Datahunt's official website does not open as of August 2026, so it was organized based on past publicly available information. As there may be changes in detailed fees and features, it is recommended to verify based on each company's official website.
The two rows to look at in the table are Main Data Area (which continent) and Maintenance Entity (who is driving). The rest is the result.
Where Is Our Company's Data Located? 5 Self-Diagnostic Questions
Check these. These five lines are faster than reading ten comparison articles.
- [ ] Is the required data publicly available information on the web, or institutional data received through personal authentication?
- [ ] Is the purpose for business data collection, or for constructing AI model training datasets?
- [ ] Is it a one-time task, or does it need to be repeated daily/weekly?
- [ ] If the site changes and data collection stops, is there someone in-house to fix it?
- [ ] Have you directly confirmed the website/operational status of the candidate companies within the last month?
If the first question is about "institutional data," this comparison itself is unnecessary — that's CODEF's continent. If it's "web public data" and needs repetitive collection with no one to fix it, the choice narrows down to managed collection.
And the fifth question. In the 2026 comparison, this is the first thing to consider.
Choosing with the Updated Map in 4 Steps
Step 1. Determine the continent of the data — Institutional structured data (accounts, transactions, certificates) should be connected via authentication-based APIs (CODEF), AI learning data construction projects (data construction companies), and continuous collection of web public data (Listly or HashScraper).
Step 2. Divide the method based on repetition — If it's a one-time or small-scale task, a self-tool is sufficient. If it needs daily/weekly repetitive collection, a method to handle operations is necessary. The overall methods are summarized in Comparing Four Methods of Web Data Extraction.
Step 3. Confirm the operator — Create collection rules, and is there someone in-house to fix the site changes? If not, it should be entrusted to a service. HashScraper includes the entire operation in a monthly subscription, operating on behalf of over 500 companies with over 5,000 site collection experiences and 99.7% data accuracy.
Step 4. Verify with the total cost for one year and operational status — Compare not just tool fees but also your time, maintenance, and data gaps (Comparing Subscription-Based Crawling vs. Individual Billing Reveals the Answer in Terms of Total Cost of Ownership (TCO) for One Year), and before signing a contract, check the operational history with 7 Verification Questions for Choosing a Web Scraping Service.
Today's task is not about selecting a service provider. Step 1 — determining the continent of your data is the first thing to do.
Frequently Asked Questions
Q. Which is more suitable for collecting financial data, Datahunt, or CODEF?
A. It depends on the type of "financial data." If the purpose is to connect institutional structured data such as accounts, transactions, and certificates through personal authentication-based APIs, then CODEF is suitable — but this is a separate field from web crawling. Datahunt used to operate in the area of constructing AI learning datasets in the financial domain, but as of August 2026, their official website does not open, so checking the operational status is essential. If it is about continuous collection of publicly available financial product information, disclosures, news, reviews, etc., then it falls under the realm of managed collection services like HashScraper.
Q. Which one, Listly or Datahunt, has a faster data collection speed?
A. The measuring axes are different. If it's about "extracting data on the current screen within a few minutes," Listly is faster. Datahunt starts with requirements negotiation and is project-based, handling a large-scale process including labeling but is slower to start (currently, operational status check is required). If you need stable speed for daily repetitive collection, managed collection is the right category rather than the two services.
Q. Should I choose a domestic service or an overseas tool?
A. If the target is primarily Korean sites, then a domestic service is advantageous. Communication in Korean and accumulated experience in dealing with Korean sites make it more favorable. HashScraper has been operating for 8 years without any legal issues related to collection.
Q. Can I use all four services together?
A. It is possible. Since they are tools from different continents rather than substitutes, it is natural to use them in combination. Using Listly for daily research, CODEF for institutional data integration, and HashScraper for regular collection of web public data is a practical combination.
Conclusion
The answer to the question, "Which of the Korean Big 4 is the best?" in 2026 is as follows.
- Extract this table into Excel immediately → Listly
- AI learning dataset construction and labeling → Data construction specialized company (Datahunt, the representative, is currently unavailable — check operational status first)
- Connection of financial/public institution data with authentication basis → CODEF (a separate field from web crawling)
- Entrusting the continuous, large-scale collection of web public data → HashScraper
HashScraper is in the fourth continent among these. For the other three questions, a different service may be the right choice.
Before choosing a service, update your map.
Start Now
If you are confused about which continent your data belongs to, just let us know the target and purpose. We will diagnose whether managed web collection is the right area or if another method is suitable for free. You can also check the data quality first with 50,000 credits when signing up.
