MEDIUMData Storagestaff engineer
Database Sharding Strategies
Explain different database sharding strategies and when to use each.
Estimated Time: 45 minutes
#databases#scalability#data-storage
Solution Overview
Sharding partitions data across multiple databases. Key strategies: hash-based, range-based, geographic, and directory-based sharding.
Solution Overview
Sharding partitions data across multiple databases. Key strategies: hash-based, range-based, geographic, and directory-based sharding.
Hints to Get Started
1
Consider your access patterns
2
Think about data growth and distribution
Strategies
geographic
cons
- •Uneven load
- •Cross-region queries complex
pros
- •Low latency
- •Data locality compliance
description
Partition by user location
hash based
cons
- •Range queries are expensive
- •Resharding is complex
pros
- •Even distribution
- •Simple to implement
description
Hash the shard key to determine shard
range based
cons
- •Hot spots possible
- •Uneven distribution
pros
- •Efficient range queries
- •Easy to understand
description
Partition by ranges of shard key
directory based
cons
- •Lookup service is bottleneck/SPOF
pros
- •Flexible
- •Easy resharding
description
Lookup service maps keys to shards
Considerations
- •Choose shard key carefully
- •Plan for resharding
- •Handle cross-shard queries