Database Sharding Explained Simply — How Facebook Scales to Billions 🗄️ #shorts

Database Sharding — the secret behind every app that handles billions of users.

Sharding splits a large database into smaller, independent parts called shards.
Each shard holds only a subset of the data.

Why Shard?
→ Scale Horizontally — handle more data by adding shards
→ Better Performance — smaller datasets = faster queries
→ High Availability — if one shard fails, others keep working
→ Cost Effective — use commodity hardware instead of expensive servers

3 Sharding Strategies:
✅ Range-Based — split by value ranges (User ID 1–1000 → Shard 1)
✅ Hash-Based — hash function decides the shard (hash(user_id) % 3)
✅ Directory-Based — lookup table maps data to the correct shard

Real-World Examples:
🔵 Facebook — shards by User ID to handle billions of users
🔴 Netflix — shards by data range to manage massive logs
🟡 Uber — uses sharding to scale geospatial data
🐦 Twitter — shards tweets data for high write throughput

Break big. Scale smart.

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Видео Database Sharding Explained Simply — How Facebook Scales to Billions 🗄️ #shorts канала Dev Kant Kumar