I wrote this technical deep-dive to explore the paradigm mismatch between declarative, set-based processing and sequential, depth-first search algorithms.

The write-up walks through the mechanics of forcing a relational database engine (DuckDB) to handle chess logic, specifically:

• Data Representation: Mapping 64-bit bitboards into a relational model using UBIGINT types.
• The Pruning Blocker: Why the stateless nature of relational sets prevents sibling nodes from communicating, making true Alpha-Beta pruning impossible inside a single query.
• The Workaround: Offloading the stateful control flow to an external orchestrator to implement Batched Principal Variation Search (PVS) across query boundaries without violating the declarative nature of the core chess math.

The resulting chess engine is obviously not competitive, but the goal was to document the architectural trade-offs, the performance walls encountered with recursive CTEs, and how relational algebra behaves when pushed entirely out of its comfort zone.