Pulsschemas

Pulsschemas is a hypothetical schema language designed to describe time-based, pulse-driven event data common in real-time streaming systems. In this model, a pulse represents a burst or window of related events that share a temporal context, such as a single sensor reading interval or a transaction batch. Pulsschemas define the structure of such bursts, including the entities involved and the fields that appear within a pulse.

The core concepts include pulse definitions, entities, and fields with typed values, as well as constraints and temporal metadata. Each field has a data type (for example string, number, boolean, timestamp) and optional qualifiers such as required, unique, or bounds. Pulses may carry metadata such as validFrom, validTo, pulseId, and pulseWindow to support temporal queries and schema evolution.

Syntax and tooling are designed to be lightweight and interoperable with existing data contracts. The schema can be expressed in JSON-like or YAML-like syntax and paired with validation tooling that checks data conformance at ingest time. Pulsschemas are intended to be compatible with common streaming platforms and can coexist with, but differ from, traditional schemas used for static datasets.

Use cases include high-frequency financial data, IoT sensor streams, and batch-like micro-events that arrive in bursts. In these contexts, pulsschemas help ensure consistent interpretation of temporally clustered data and support schema evolution without breaking consumers.

The concept remains informal and not widely standardized. Proponents cite clearer temporal semantics and improved validation, while critics point to limited tooling, potential duplication of features in existing schemas, and the challenge of integrating with established data models.