What is Database Sharding?
Database sharding is a horizontal partitioning technique that splits a large database into smaller, faster, more manageable parts called shards. Each shard holds a subset of the data and operates as an independent database.
Sharding Strategies
- Key-Based Sharding: Data is distributed based on a shard key (e.g., user ID)
- Range-Based Sharding: Data is split based on ranges of values
- Directory-Based Sharding: A lookup table determines which shard stores which data
Benefits
- Horizontal Scaling: Add more servers to handle increased load
- Improved Performance: Queries are faster on smaller datasets
- High Availability: Failure of one shard doesn’t affect others
Challenges
- Complex Queries: Cross-shard queries are difficult
- Rebalancing: Adding/removing shards requires data migration
- Operational Complexity: More servers to manage