Database partitioning is about logically splitting one large table into smaller physical pieces, such that improving query performance. DB partitioning is a good alternate for indexing multiple columns, reducing index size, hence the memory in use. Few common pros of database partitioning:
- Improved performance – data operations (CRUD) can be performed on a smaller volume of data, for example, in case of collecting data overtime, putting old data in separate partition might help with performance.
- Bulk create and delete can be efficient by adding or removing separate partitions.
- Time based partition can be helpful in cleaning old seldom-used data i.e. month based partition we can simply set a cron job for cleaning 12 month old partition, without effecting the table portion heavily in use for ADD, UPDATE, etc.
- Improved scalability – In case of very large tables, you can partition and have them hosted on a separate server.
There are 2 main approaches to database partitioning:
- Horizontal partitioning (Sharding) – a table is split horizontally, such that each partition is a subset of the table, having the same schema (i.e. number of fields/columns).
- Vertical partitioning – a table is split on the fields/columns, such that each subset has separate schema. A common use-case for vertical partitioning is to partition table fields on the basis of pattern of use i.e. frequently accessed fields are to be grouped together, and the less frequently accessed are put in a separate partition.