Real-World Sharding: How the Giants Do It

Let's see how real companies solve sharding in practice. These aren't theoretical examples - this is how the internet actually works!

Instagram's User Sharding:

• Shard by user ID: shard_id = user_id % 4000
• Each shard handles ~1000 users
• Photos, comments, likes all stay with the user's shard
• Cross-shard queries? Almost never needed!

Discord's Message Sharding:

• Shard by channel ID: keeps all messages in a channel together
• When you load a chat, everything comes from one shard
• Super fast message loading
• Users never notice messages are split across continents

Uber's Geographic Sharding:

• Shard by city: New York rides in New York shard
• Makes perfect sense - rides rarely span cities
• Each city's database can be optimized independently
• Natural disaster in one city? Other cities unaffected

The Common Pattern: All successful sharding strategies follow one rule - keep related data together on the same shard.

Key Insight: "The best sharding strategies mirror how users actually use your application - if data is accessed together, it should live together."