Hive Partitioned vs Bucketed Tables Explained

Hive partitioned tables and bucketed tables are two different ways of storing and managing data, and they have the following differences:

1. Partitioned table: In Hive, a partitioned table is a table that stores data based on specified column values, allowing for fast retrieval and querying of data based on partition column values. The data in partitioned tables is stored in different directories for easy management and maintenance. Partitioned tables can improve query performance and reduce the amount of data scanned.
2. Bucketed table: This type of table stores data by bucketing it based on specified column values, evenly distributing the data into multiple buckets. Bucketed tables can improve query performance, reduce data skewness, and address skewness issues between partitions. They are suitable for use with large volumes of data, enhancing query efficiency.

In general, partitioning tables involves storing data based on a column value for logical organization, while bucketing tables evenly distribute data across multiple buckets for storage. Both methods can enhance query performance and streamline data management efficiency.