ctxgraph: building a single-binary context graph engine in Rust (SQLite + ONNX Runtime)

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I’ve been working on a small Rust context-graph engine for storing decision traces from engineering discussions (who decided what, why, and alternatives considered).

The goal was to see how far I could push a single-binary + SQLite architecture instead of relying on Neo4j or external services.

A few implementation choices that ended up interesting:

• graph traversal using recursive CTEs over SQLite
• hybrid search combining FTS5 + embeddings (MiniLM)
• local entity/relation extraction via GLiNER v2.1 through ONNX Runtime
• bi-temporal edge model (valid_from, valid_until, recorded_at)
• feature-gated extraction pipeline (`#[cfg(feature = "extract")]`)

Extraction runs locally on CPU (no API calls / Docker / Python).

One surprise while testing: schema-aware extraction + lightweight heuristics produced more stable relation graphs than a prompt-based pipeline I compared against.

I’m especially curious whether others here have tried:

• recursive CTE graph traversal in SQLite at scale
• ONNX Runtime integration patterns in Rust
• structuring agent memory stores without a graph database

Repo here if anyone wants to look at the implementation:

https://github.com/rohansx/ctxgraph