Case Study · Graph Systems
Holocron Timeline Engine
A graph-backed timeline system that models events and causal dependencies in Neo4j, then supports traversal-heavy reads, break simulation, and world-state reconstruction.
This project let me work on a class of system that standard CRUD apps rarely touch: graph traversal, mutation replay, and simulation logic over request-scoped subgraphs.
Core model
Events as nodes, causal links as edges, state change represented through mutation relationships
Simulation
What-if break propagation through downstream dependencies in topological order
Replay
Universe state rebuilt from baseline state plus ordered prior mutations
What I built
Built the full stack across a Next.js frontend, FastAPI backend, and Neo4j graph store, including traversal, validation, simulation, and replay logic.
Results
Hard problems
Chronology normalization across BBY/ABY boundaries
The backend stores chronology as signed integers with an internal zero so filtering, sorting, interval math, and replay can all work on a continuous numeric axis.
Break simulation over downstream causal graphs
The simulation service computes a topological order over the downstream subgraph, then marks events as invalidated or unresolved based on surviving dependencies.
State reconstruction without snapshotting every node
Instead of storing full snapshots on graph nodes, the system replays curated state mutations in chronology order and uses checkpoints to reduce repeated replay cost.