Telegram Scraper 2.0: Blazing-Fast, Scalable OSINT Tool for Real-Time Channel Data Extraction

Hazem Abbas

23 Jul 2025 — 2 min read

Is Telegram a Goldmine for Information?

Short Answer, Absolutely.

But what if you could mine it 10x faster, without crashing, throttling, or compromising security ?

Introducing Telegram Scraper 2.0, the most powerful, efficient, and developer-friendly Python tool yet for extracting messages and media from public Telegram channels .

Built on Telethon , this open-source scraper is a game-changer for OSINT professionals, researchers, journalists, and data analysts .

And yes, it’s blazing fast . But more importantly: it's secure, respectful of API limits, and privacy-conscious .

Built for Real-World Use: Key Features

Faster & Smarter Scraping

5–10x faster message scraping with batch database inserts
3x faster media downloads using parallel processing (up to 3 at once)
10–20x faster database performance thanks to connection pooling
No memory crashes, exports stream data directly (great for 100K+ messages)

Better User Experience

See exact message counts before scraping
Clear progress tracking : percentages, message count, and time remaining
Simple interactive menu, easy to use, no coding needed

Reliable & Resilient

Resume from where it stopped, saves progress every 50 messages
Auto-retry system: handles network issues and rate limits intelligently
Flood control protection: respects Telegram’s limits, avoids bans

Developer-Friendly

Clean object-oriented code: easy to extend or contribute to
Configurable settings: adjust download speed, concurrency, and paths
Optimized database with indexes: fast queries and storage

Export & Store

Save data to JSON or CSV: ready for analysis
Messages stored in SQLite, lightweight and reliable
Re-download failed media with reprocessing support

Data Storage

Database Structure

Data is stored in SQLite databases, one per channel with optimized indexes:

Location: ./channelname/channelname.db
Table: messages
- id: Primary key
- message_id: Telegram message ID (indexed)
- date: Message timestamp (indexed)
- sender_id: Sender's Telegram ID
- first_name: Sender's first name
- last_name: Sender's last name
- username: Sender's username
- message: Message text
- media_type: Type of media (if any)
- media_path: Local path to downloaded media
- reply_to: ID of replied message (if any)