deduplicate

Deduplicate, or dedup, refers to techniques that identify and remove duplicate copies of data, reducing storage requirements and, in some cases, bandwidth usage. It is widely used in backup systems, cloud storage, file systems, and data management pipelines.

Dedup methods operate by detecting identical data units and replacing duplicates with references to a single stored copy. The process can be performed online (inline) as data is written, or offline (post-process) after data has been stored. Data is divided into chunks, which can be fixed-size or variable-size depending on the algorithm. Each chunk is hashed to produce a fingerprint; identical fingerprints indicate duplicates. Unique chunks are stored in a content-addressable store, while metadata or pointers record how to assemble the original data when read back.

There are several levels of deduplication. File-level dedup checks entire files for duplicates. Block-level dedup partitions data into smaller blocks; byte-level dedup operates on even finer granularity. Variable-sized chunking, such as content-defined chunking, helps preserve dedup across edits and shifts in data, improving savings.

Benefits include reduced storage capacity, lower bandwidth for data transfer and replication, and faster backups and restores in many scenarios. However, deduplication adds processing overhead, requires additional metadata management, and can complicate data loss scenarios if a central pointer store is damaged. Some workloads experience diminishing returns depending on data similarity and retention patterns.

Applications span backup and disaster recovery, archival storage, virtualization, and cloud storage services. Effective deduplication typically pairs with data integrity checks (hashes, checksums) to detect corruption and avoid incorrect reconstructions.