How It Works
- Paste Your Text: Input any text containing URLs (https://example.com), email addresses ([email protected]), or naked domain mentions (example.com) into the text area.
- Configure Options: Choose whether to include subdomains (www.example.com vs example.com), show occurrence counts, and sort results alphabetically.
- Extract Domains: The tool uses regex patterns to identify all domain formats including URLs, email addresses, and plain domain mentions across multiple TLDs (.com, .org, .io, etc.).
- Review Results: Get a clean list of unique domains with statistics showing total occurrences, unique count, and top domains by frequency.
Manual vs Automated Domain Extraction
| Feature | Manual Extraction | AI-Powered Extractor |
|---|---|---|
| Extraction Speed | Manually find and copy domains | Instant extraction from any text |
| Format Detection | Miss domains in emails or URLs | Detects URLs, emails, naked domains |
| Subdomain Handling | Manually decide on subdomains | Toggle to include/exclude subdomains |
| Deduplication | Manually remove duplicates | Auto-removes duplicates with counts |
| TLD Support | Limited to common TLDs | Supports all TLDs (.com, .io, .dev, etc.) |
| Statistics | No occurrence tracking | Shows frequency and top domains |
Domain Extraction Examples
Example 1: Extract from Mixed Text
Visit https://www.example.com for more info.
Contact us at [email protected]
Check out blog.company.io and api.service.net
Email: [email protected]example.com (2 occurrences)
testsite.org (1 occurrence)
company.io (1 occurrence)
service.net (1 occurrence)
Statistics:
- Unique Domains: 4
- Total Occurrences: 5Key Changes:
The extractor identifies domains from multiple formats: full URLs with protocols (https://www.example.com), email addresses ([email protected]), and subdomain mentions (blog.company.io). It automatically deduplicates entries, counting that example.com appears twice across different contexts. The tool recognizes various TLDs (.com, .org, .io, .net) and can optionally strip subdomains to show root domains only. This is particularly useful for SEO backlink analysis where you need to identify unique referring domains regardless of subdomain variations. The occurrence count helps prioritize domains by frequency, essential for link audit workflows and competitor analysis.
Example 2: Extract from Log Files
192.168.1.1 - - [01/Jan/2024] "GET / HTTP/1.1" 200 - "https://google.com"
192.168.1.2 - - [01/Jan/2024] "GET /page HTTP/1.1" 200 - "https://facebook.com"
192.168.1.3 - - [01/Jan/2024] "POST /api HTTP/1.1" 201 - "https://twitter.com"
192.168.1.1 - - [01/Jan/2024] "GET /about HTTP/1.1" 200 - "https://google.com"google.com (2 occurrences)
facebook.com (1 occurrence)
twitter.com (1 occurrence)
Top Referrers:
1. google.com - 50% of traffic
2. facebook.com - 25% of traffic
3. twitter.com - 25% of trafficKey Changes:
When processing server logs, the domain extractor automatically parses referrer URLs to identify traffic sources. It handles Apache/Nginx log formats, extracting domains from the referrer field while ignoring IP addresses and other log metadata. The tool's deduplication and counting features are crucial for traffic analysis, showing that google.com referred 50% of requests in this sample. This is invaluable for web analytics, helping identify top referral sources without manual parsing. The extractor works with large log files (processing thousands of lines instantly) and can handle various log formats including JSON logs, making it a versatile tool for DevOps and analytics teams analyzing traffic patterns and referral sources.
Frequently Asked Questions
What domain formats can it extract?
The extractor handles full URLs with protocols (http://, https://), email addresses ([email protected]), naked domains (example.com), and subdomains (blog.example.com). It recognizes all standard TLDs including .com, .org, .net, .io, .dev, and country-code TLDs like .co.uk. The tool uses comprehensive regex patterns that match RFC 1034/1035 domain name specifications, ensuring accurate extraction from any text format including HTML, logs, CSV files, and plain text. You can configure whether to preserve subdomains or extract root domains only, making it flexible for different use cases like SEO analysis (where root domains matter) or security audits (where subdomains are important).
Is my data secure when extracting domains?
Absolutely secure. All domain extraction happens entirely in your browser using JavaScript regex processing. No text is uploaded to any server, and no data is stored or logged. The tool works completely offline once loaded, making it safe for processing sensitive data like internal server logs, customer email lists, or confidential documents. This client-side architecture ensures GDPR compliance and protects proprietary information. You can even disconnect from the internet after loading the page and the extractor will continue to function, proving that zero data leaves your machine during the extraction process.
Can it handle large text files and bulk extraction?
Yes, the extractor efficiently processes large documents including multi-megabyte log files, email archives, and data dumps. It uses optimized regex patterns with linear time complexity O(n) for scanning text, making it fast even with millions of characters. For very large files (100MB+), consider processing in chunks to avoid browser memory limits. The tool automatically handles duplicate removal using JavaScript Set data structures for O(1) lookup performance, ensuring instant deduplication even with thousands of domains. The occurrence counting feature uses hash maps for efficient frequency tracking, and results can be sorted alphabetically or by frequency to quickly identify top domains in large datasets.