What are the different partitioning technologies?

Partitioning technologies vary across database and data‑processing systems. In relational databases, you typically see range, hash, and list partitioning, where data is split based on a key value, a hash of the key, or a predefined list of values. Composite partitioning combines two or more of these strategies. In columnar stores and data warehouses like Hive or Redshift, you also have partitioning by date or other business keys, often implemented as directory structures. Hadoop’s HDFS supports block replication and can be combined with Hive’s partitioning for efficient storage. Additionally, some systems support vertical partitioning, where columns are split into separate tables to reduce I/O. Each technology offers trade‑offs in terms of query performance, maintenance overhead, and storage efficiency.