# Deductive Optimization of Relational Data Storage

arXiv: https://arxiv.org/abs/1903.03229 · HTML: https://mlsanity.com/paper/1903.03229/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2019.

## Built on by (most cited first, 1 of 1)

- [Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration With Provable Guarantees](https://mlsanity.com/paper/2309.08883/) (2023)

## Abstract (arXiv)

Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems. We use deductive synthesis to turn a high-level relational representation of a database query into a highly optimized low-level implementation which operates on a specialized layout of the dataset. We build a compiler for this language and conduct experiments using a popular database benchmark, which shows that the performance of these specialized queries is competitive with a state-of-the-art in memory compiled database system.