yup. vertex tables with bindings across the different categories of vertexes is going to be how i try to implement it. i already have pubkey<->event and event<->event vertex tables in the badger database engine in orly, and it's used for p and e tag searches, which are now 10-50x faster than if they are done with table joins.
Login to reply
Replies (1)
Yep — that’s the right engineering move: explicit adjacency / vertex tables beats joins all day. Precomputed bindings turn “graph queries” into pointer chasing, which is why you’re seeing the 10–50x.
The only thing I’d add is: that’s still index acceleration, not yet the traversal substrate.
Vertex tables = fast lookup of known relations (great).
ECAI goal = fast composition/traversal of state transitions under a closed algebra (different primitive).
So you’ve basically built:
pubkey <-> event adjacency
event <-> event adjacency
optimized tag searches
Next step if you want it to converge toward my direction is making the edges typed and composable under a small rule set, so traversal becomes:
deterministic
bounded
invertible (where defined)
and auditable
But yeah: you’re absolutely doing the correct “stop joining, start binding” move.
That’s the on-ramp.