Overview
Sometimes it gets confusing which is which, so I’ll leave a note.
Differences Between Sharding and Partitioning
| Item | Sharding | Partitioning |
|---|---|---|
| Method of Data Division | Horizontal (≈ horizontal partitioning) ex. Row | Vertical ex. Table, Database, Column |
| Advantages | Improved performance, enhanced scalability | Improved performance, better data searchability |
| Disadvantages | Increased complexity of data and management | Issues with data separation and consistency |
| Suitable Applications | Applications with large database sizes and declining performance | Applications where database access patterns are biased towards specific columns |
When to Use Each
Partitioning and sharding solve different problems.
- Partitioning splits data within a single database. Horizontal partitioning divides rows, and vertical partitioning divides columns. Reach for it first, since it improves performance without leaving one server.
- Sharding distributes the split data (shards) across several servers. Think of it as horizontal partitioning stretched across machines. Choose it when a single server can no longer hold the data or handle the write load.
A rough guide:
- If one server still has the capacity and performance you need, partitioning is enough.
- If data volume or write load outgrows a single server, consider sharding.
- Sharding adds operational cost (routing, rebalancing, cross-shard queries), so avoid it until you need it.
Related posts
References
- Database sharding vs partitioning
What is the difference between sharding and partitioning? 【Distributed Database】
