Deltaeach

Deltaeach is a term used in information technology and data management to describe a technique for representing and propagating changes at the level of individual elements within a collection. It emphasizes per-element deltas rather than a single coarse delta for the whole dataset.

The word delta comes from mathematics meaning change, and each indicates per-element granularity. The term is not widely standardized and appears mainly in niche blogs, project documentation, and discussions about incremental data processing.

In practice, deltaeach involves computing, storing, or transmitting a delta for each element that has changed since a reference state. Implementations vary: some compute diffs against previous versions, others track timestamps and version vectors, and still others hash elements to detect which items differ. The approach supports incremental updates, selective synchronization, and streaming analytics.

Applications include collaborative editing, database replication, sensor networks, and machine learning pipelines that update models based on streaming data without reprocessing the entire dataset.

Advantages include reduced bandwidth and faster updates for large collections; drawbacks include added bookkeeping, robustness concerns with out-of-order updates, and potential complexity in merge semantics.

See also delta encoding, change data capture, incremental learning, and event sourcing.