#📝 Note: Database Sharding

#Overview

Sharding is a database architecture pattern that involves breaking a large database into smaller, more manageable parts called shards. Each shard is a separate database, and collectively, they hold the entire dataset.

#Why Shard?

• Horizontal Scalability: Distribute load across multiple servers.
• Improved Performance: Smaller datasets per server lead to faster queries.
• Availability: A failure in one shard doesn't affect the entire system.

#Sharding Strategies

• Key-based (Hash) Sharding: Use a hash of a key (e.g., user_id) to determine the shard.
• Range-based Sharding: Assign shards based on ranges of a value (e.g., A-M, N-Z).
• Directory-based Sharding: Maintain a lookup table to map keys to shards.

#Trade-offs

• Complexity: Application logic must handle shard routing.
• Resharding: Moving data between shards is difficult.
• Joins: Performing joins across shards is very expensive and often avoided.