What problem does it solve?
It eliminates the complexity of maintaining up-to-date derived state when in-memory relational data changes, so query results stay synchronized with incremental updates instead of requiring full recomputation.
Core Features & Use Cases
- Incremental view + delta model: Represents each derived mapping as a current snapshot (view) plus a change sequence (delta), enabling correct propagation through combinators.
- Composable query operators: Supports operators like map, filter/map, chain, join, union to build incremental computation pipelines over key→value and key→many data.
- FK fanout for relational change propagation: Uses a reverse multi-query (TriQuery) to propagate changes across foreign-key relationships efficiently.
- Batch change handling: Provides DataChanges abstractions and bridges from ValueChange-based deltas for batch processing workflows.
- Validation helpers: Includes consistency checks for Query/MultiQuery behaviors (iter/access hints).
Quick Start
Use the query-system skill to design an incremental renderer pipeline where database writes produce deltas, combinators compute derived state, and fanout propagates FK updates to keep GPU-related inputs synchronized.