What term describes the method of compressing indexed data in Splunk?

The method of compressing indexed data in Splunk is termed "data bucketing." In Splunk, data is organized into buckets, which are distinct directories that contain indexed data. These buckets are categorized based on their age and state (such as hot, warm, cold, or frozen) and serve to manage the lifecycle of data.

When data is ingested into Splunk, it is initially placed into a hot bucket. As the data ages, it transitions through warm and cold states, during which time Splunk applies compression algorithms to reduce the storage footprint of the indexed data. This process helps in efficient storage management and retrieval of data, optimizing performance while ensuring that older, less frequently accessed data does not occupy excessive resources.

The other options do not specifically relate to the mechanism of compressing indexed data in the same way. Data redundancy refers to unnecessary duplication of data, data indexing is the process of organizing data for efficient retrieval, and data archiving usually involves moving data to a storage system for long-term retention without the active retrieval features of indexed data. Thus, "data bucketing" is the term that accurately describes the method used in Splunk for the organized and compressed storage of indexed data.