Definition:
- Partitioning is the process of dividing a single database table into smaller, more manageable pieces called partitions. Each partition is stored within the same database but as a separate table or file.
Purpose:
- It is used to improve performance and manageability of large tables by splitting them into smaller, more manageable parts.
Implementation:
- Data is divided based on a partition key, which determines the distribution of data across different partitions.
- Partitions can be created based on various strategies such as range, list, hash, or composite.
Characteristics:
- Partitions typically reside on the same database server or cluster.
- All partitions are part of the same database schema.
- Queries can be optimized to target specific partitions, reducing the amount of data scanned.
Use Cases:
- Databases with very large tables where querying and managing data becomes inefficient.
- Scenarios requiring efficient access to specific subsets of data, such as time-series data, regional data, or categorical data.
Advantages:
- Improved query performance by reducing the amount of data scanned.
- Easier management of large tables by operating on partitions independently.
- Enhanced maintenance tasks such as backup, restore, and archiving on a per-partition basis.
Disadvantages:
- Limited scalability compared to sharding, as partitions usually reside on the same server.
- Potential complexity in partition management and maintenance.
- Requires careful design of the partition key to ensure even data distribution.
Type of partitioning:
- Horizontal
- Vertical