tapbranch

Tapbranch is a conceptual model used in data processing and software design to describe a mechanism for recording where a data stream is tapped and branched into parallel workflows, while preserving the overall lineage of events. The term combines the idea of tapping data streams with branching execution paths, emphasizing non-destructive observation and traceability.

In this model, the main primitives are tappoints, branches, and merges. A tappoint is a location where a data item or event is observed without altering the primary flow. A branch represents an alternate processing path that may handle a subset of events or apply different logic. A merge reconciles data from multiple branches back into a single stream, optionally applying conflict resolution and versioning. Checkpoints provide reproducible restart points, allowing replay from known states if needed. Events carry metadata such as timestamps, branch identifiers, and lineage pointers to enable deterministic replay and audit trails.

Tapbranch is used to design and reason about streaming pipelines, event-sourced systems, and data lineage frameworks. It supports scenarios such as parallel processing, auditing, debugging, and experimental experimentation within a single coherent stream. Benefits include non-intrusive data observation, modular pipeline composition, deterministic replay, and improved traceability across complex workflows. Environments that require reproducibility and auditability, such as telemetry, analytics, and compliance-focused data platforms, may leverage tapbranch-inspired patterns to manage branching without duplicating data or breaking the main flow.

Limitations include added complexity in maintaining consistent state across branches and potential performance overhead from metadata tracking. Variants of the concept exist in different streaming and event-sourcing ecosystems, each adapting the primitives to its own data models and guarantees. See also: data lineage, event sourcing, stream processing, branching.