Why Vector Databases Fall Short on Multi-Table Join Analytics
Vector embeddings are ideal for semantic search, but catastrophic for relational joins, aggregations, and exact financial balance calculations.
Many teams attempt to build enterprise 'chat with your data' tools by dumping tabular data into vector databases (RAG). While this works well for unstructured documents and FAQs, it fails completely when calculating numbers like 'Total Q3 revenue grouped by customer tier'.
Vector databases do not understand foreign key relationships, exact decimal arithmetic, or SQL aggregate grouping. They produce probabilistic guesses rather than deterministic mathematical truth.
ZeroQueries operates directly at the relational layer using deterministic SQL compilation, ensuring that 2 + 2 always equals 4, with zero hallucination in mathematical summaries.