GenDB: The Next Generation of Query Processing -- Synthesized, Not Engineered

Researchers propose GenDB, a revolutionary database system that uses Large Language Models to synthesize query execution code instead of relying on traditional engineered query processors. Early prototype testing shows GenDB outperforms established systems like DuckDB, Umbra, and PostgreSQL on OLAP workloads.

• →GenDB uses LLMs to generate custom query execution code for each incoming query rather than maintaining complex query processing engines.
• →The system creates instance-optimized code tailored to specific data, workloads, and hardware resources.
• →Early prototype using Claude Code Agent demonstrates superior performance compared to state-of-the-art query engines including DuckDB and ClickHouse.
• →The approach addresses the challenge of rapidly evolving user requirements that traditional database systems struggle to accommodate.
• →This represents a potential paradigm shift from engineered database systems to AI-synthesized query processing.